Search results for: education management

Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

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Authors: Merrick Lopez, Aashish Abraham, Melissa Egge, Marissa Hood, Jui Shah

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A 3 year old male with unknown medical history presented initially with encephalopathy, intubated for respiratory failure, and admitted to the pediatric intensive care unit (PICU) with refractory shock. During resuscitation in the emergency department, he was found to be in severe metabolic acidosis with a pH of 7.03 and escalated on vasopressor drips for hypotension. His initial sodium was 174. He was noted to have burn injuries to his scalp, forehead, right axilla, bilateral arm creases and lower legs. He had rhabdomyolysis (initial creatinine kinase 5,430 U/L with peak levels of 62,340 normal <335 U/L), cardiac injury (initial troponin 88 ng/L with peak at 145 ng/L, normal <15ng/L), hypernatremia (peak 174, normal 140), hypocalcemia, liver injury, acute kidney injury, and neuronal loss on magnetic resonance imaging (MRI). Soft restraints and a shock collar were found in the home. He was critically ill for 8 days, but was gradually weaned off drips, extubated, and started on feeds. Discussion Electrical injury, specifically lightning injury is an uncommon but devastating cause of injury in pediatric patients. This patient with suspected abusive use of a dog shock collar presented similar to a lightning strike. Common entrance points include the hands and head, similar to our patient with linear wounds on his forehead. When current enters, it passes through tissues with the least resistance. Nerves, blood vessels, and muscles, have high fluid and electrolyte content and are commonly affected. Exit points are extremities: our child who had circumferential burns around his arm creases and ankles. Linear burns preferentially follow areas of high sweat concentration, and are thought to be due to vaporization of water on the skin’s surface. The most common cause of death from a lightning strike is due to cardiopulmonary arrest. The massive depolarization of the myocardium can result in arrhythmias and myocardial necrosis. The patient presented in cardiogenic shock with evident cardiac damage. Electricity going through vessels can lead to vaporization of intravascular water. This can explain his severe hypernatremia. He also sustained other internal organ injuries (adrenal glands, pancreas, liver, and kidney). Electrical discharge also leads to direct skeletal muscle injury in addition to prolonged muscular spasm. Rhabdomyolysis, the acute damage of muscle, leads to release of potentially toxic components into the circulation which could lead to acute renal failure. The patient had severe rhabdomyolysis and renal injury. Early hypocalcemia has been consistently demonstrated in patients with rhabdomyolysis. This was present in the patient and led to increased vasopressor needs. Central nervous system injuries are also common which can include encephalopathy, hypoxic injury, and cerebral infarction. The patient had evidence of brain injury as seen on MRI. Conclusion Electrical injuries due to lightning strikes and abusive use of a dog shock collar are rare, but can both present in similar ways with respiratory failure, shock, hypernatremia, rhabdomyolysis, brain injury, and multiorgan damage. Although rare, it is essential for early identification and prompt management for acute and chronic complications in these children.

Keywords: cardiogenic shock, dog shock collar, lightning strike, rhabdomyolysis

Procedia PDF Downloads 88

Authors: Siddhant Yadav, Rylea Ranum, Hannah Alberts, Abdul Kalaiger, Brent Bauer, Ryan Hurt, Ann Vincent, Loren Toussaint, Sanjeev Nanda

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Background and significance: Fibromyalgia (FM) is a chronic pain disorder also characterized by chronic fatigue, morning stiffness, sleep, and cognitive symptoms, psychological disturbances (anxiety, depression), and is comorbid with multiple medical and psychiatric conditions. It has an incidence of 2-4% in the general population and is reported more commonly in women. Oxidative stress and inflammation are thought to contribute to pain in patients with FM, and the adoption of an antioxidant/anti-inflammatory diet has been suggested as a modality to alleviate symptoms. The aim of this systematic review was to evaluate the efficacy of specialized diets (ketogenic, gluten free, Mediterranean, and low carbohydrate) in improving FM symptoms. Methodology: A comprehensive search of the following databases from inception to July 15th, 2021, was conducted: Ovid MEDLINE and Epub ahead of print, in-process and other non-indexed citations and daily, Ovid Embase, Ovid EBM reviews, Cochrane central register of controlled trials, EBSCO host CINAHL with full text, Elsevier Scopus, website and citation index, web of science emerging sources citation and clinicaltrials.gov. We included randomized controlled trials, non-randomized experimental studies, cross-sectional studies, cohort studies, case series, and case reports in adults with fibromyalgia. The risk of bias was assessed with the Agency for Health Care Research and Quality designed, specific recommended criteria (AHRQ). Results: Thirteen studies were eligible for inclusion. This included a total of 761 participants. Twelve out of the 13 studies reported improvement in widespread body pain, joint stiffness, sleeping pattern, mood, and gastrointestinal symptoms, and one study reported no changes in symptomatology in patients with FM on specialized diets. None of the studies showed the worsening of symptoms associated with a specific diet. Most of the patient population was female, with the mean age at which fibromyalgia was diagnosed being 48.12 years. Improvement in symptoms was reported by the patient's adhering to a gluten-free diet, raw vegan diet, tryptophan- and magnesium-enriched Mediterranean diet, aspartame- and msg- elimination diet, and specifically a Khorasan wheat diet. Risk of bias assessment noted that 6 studies had a low risk of bias (5 clinical trials and 1 case series), four studies had a moderate risk of bias, and 3 had a high risk of bias. In many of the studies, the allocation of treatment (diets) was not adequately concealed, and the researchers did not rule out any potential impact from a concurrent intervention or an unintended exposure that might have biased the results. On the other hand, there was a low risk of attrition bias in all the trials; all were conducted with an intention-to-treat, and the inclusion/exclusion criteria, exposures/interventions, and primary outcomes were valid, reliable, and implemented consistently across all study participants. Concluding statement: Patients with fibromyalgia who followed specialized diets experienced a variable degree of improvement in their widespread body pain. Improvement was also seen in stiffness, fatigue, moods, sleeping patterns, and gastrointestinal symptoms. Additionally, the majority of the patients also reported improvement in overall quality of life.

Keywords: fibromyalgia, specialized diet, vegan, gluten free, Mediterranean, systematic review

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Authors: Abdulkarim Nasir, Alhassan T. Yahaya, Hauwa T. Abdulkarim, Abdussalam El-Suleiman, Yakubu K. Abubakar

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The need for sustainable and reliable electricity supply in rural communities of Nigeria remains a pressing issue, given the country's vast energy deficit and the significant number of inhabitants lacking access to electricity. This research focuses on the development of a portable hybrid renewable energy system designed to provide a sustainable and efficient electricity supply to these underserved regions. The proposed system integrates multiple renewable energy sources, specifically solar and wind, to harness the abundant natural resources available in Nigeria. The design and development process involves the selection and optimization of components such as photovoltaic panels, wind turbines, energy storage units (batteries), and power management systems. These components are chosen based on their suitability for rural environments, cost-effectiveness, and ease of maintenance. The hybrid system is designed to be portable, allowing for easy transportation and deployment in remote locations with limited infrastructure. Key to the system's effectiveness is its hybrid nature, which ensures continuous power supply by compensating for the intermittent nature of individual renewable sources. Solar energy is harnessed during the day, while wind energy is captured whenever wind conditions are favourable, thus ensuring a more stable and reliable energy output. Energy storage units are critical in this setup, storing excess energy generated during peak production times and supplying power during periods of low renewable generation. These studies include assessing the solar irradiance, wind speed patterns, and energy consumption needs of rural communities. The simulation results inform the optimization of the system's design to maximize energy efficiency and reliability. This paper presents the development and evaluation of a 4 kW standalone hybrid system combining wind and solar power. The portable device measures approximately 8 feet 5 inches in width, 8 inches 4 inches in depth, and around 38 feet in height. It includes four solar panels with a capacity of 120 watts each, a 1.5 kW wind turbine, a solar charge controller, remote power storage, batteries, and battery control mechanisms. Designed to operate independently of the grid, this hybrid device offers versatility for use in highways and various other applications. It also presents a summary and characterization of the device, along with photovoltaic data collected in Nigeria during the month of April. The construction plan for the hybrid energy tower is outlined, which involves combining a vertical-axis wind turbine with solar panels to harness both wind and solar energy. Positioned between the roadway divider and automobiles, the tower takes advantage of the air velocity generated by passing vehicles. The solar panels are strategically mounted to deflect air toward the turbine while generating energy. Generators and gear systems attached to the turbine shaft enable power generation, offering a portable solution to energy challenges in Nigerian communities. The study also addresses the economic feasibility of the system, considering the initial investment costs, maintenance, and potential savings from reduced fossil fuel use. A comparative analysis with traditional energy supply methods highlights the long-term benefits and sustainability of the hybrid system.

Keywords: renewable energy, solar panel, wind turbine, hybrid system, generator

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

Procedia PDF Downloads 867

Authors: Yung-Chih Kuo, Che-Yu Lin, Jay-Shake Li, Yung-I Lou

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Curcumin (CRM) and nerve growth factor (NGF) were entrapped in liposomes (LIP) with cardiolipin (CL) to downregulate the phosphorylation of mitogen-activated protein kinases for Alzheimer’s disease (AD) management. AD belongs to neurodegenerative disorder with a gradual loss of memory, yielding irreversible dementia. CL-conjugated LIP loaded with CRM (CRM-CL/LIP) and that with NGF (NGF-CL/LIP) were applied to AD models of SK-N-MC cells and Wistar rats with an insult of β-amyloid peptide (Aβ). Lipids comprising 1,2-dipalmitoyl-sn-glycero-3- phosphocholine (Avanti Polar Lipids, Alabaster, AL), 1',3'-bis[1,2- dimyristoyl-sn-glycero-3-phospho]-sn-glycerol (CL; Avanti Polar Lipids), 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-N- [methoxy(polyethylene glycol)-2000] (Avanti Polar Lipids), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(polyethylene glycol)-2000] (Avanti Polar Lipids) and CRM (Sigma–Aldrich, St. Louis, MO) were dissolved in chloroform (J. T. Baker, Phillipsburg, NJ) and condensed using a rotary evaporator (Panchum, Kaohsiung, Taiwan). Human β-NGF (Alomone Lab, Jerusalem, Israel) was added in the aqueous phase. Wheat germ agglutinin (WGA; Medicago AB, Uppsala, Sweden) was grafted on LIP loaded with CRM for (WGA-CRM-LIP) and CL-conjugated LIP loaded with CRM (WGA-CRM-CL/LIP) using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (Sigma–Aldrich) and N-hydroxysuccinimide (Alfa Aesar, Ward Hill, MA). The protein samples of SK-N-MC cells (American Type Tissue Collection, Rockville, MD) were used for sodium dodecyl sulfate (Sigma–Aldrich) polyacrylamide gel (Sigma–Aldrich) electrophoresis. In animal study, the LIP formulations were administered by intravenous injection via a tail vein of male Wistar rats (250–280 g, 8 weeks, BioLasco, Taipei, Taiwan), which were housed in the Animal Laboratory of National Chung Cheng University in accordance with the institutional guidelines and the guidelines of Animal Protection Committee under the Council of Agriculture of the Republic of China. We found that CRM-CL/LIP could inhibit the expressions of phosphorylated p38 (p-p38), p-Jun N-terminal kinase (p-JNK), and p-tau protein at serine 202 (p-Ser202) to retard the neuronal apoptosis. Free CRM and released CRM from CRM-LIP and CRM-CL/LIP were not in a straightforward manner to effectively inhibit the expression of p-p38 and p-JNK in the cytoplasm. In addition, NGF-CL/LIP enhanced the quantities of p-neurotrophic tyrosine kinase receptor type 1 (p-TrkA) and p-extracellular-signal-regulated kinase 5 (p-ERK5), preventing the Aβ-induced degeneration of neurons. The membrane fusion of NGF-LIP activated the ERK5 pathway and the targeting capacity of NGF-CL/LIP enhanced the possibility of released NGF to affect the TrkA level. Moreover, WGA-CRM-LIP improved the permeation of CRM across the blood–brain barrier (BBB) and significantly reduced the Aβ plaque deposition and malondialdehyde level and increased the percentage of normal neurons and cholinergic function in the hippocampus of AD rats. This was mainly because the encapsulated CRM was protected by LIP against a rapid degradation in the blood. Furthermore, WGA on LIP could target N-acetylglucosamine on endothelia and increased the quantity of CRM transported across the BBB. In addition, WGA-CRM-CL/LIP could be effective in suppressing the synthesis of acetylcholinesterase and reduced the decomposition of acetylcholine for better neurotransmission. Based on the in vitro and in vivo evidences, WGA-CRM-CL/LIP can rescue neurons from apoptosis in the brain and can be a promising drug delivery system for clinical AD therapy.

Keywords: Alzheimer’s disease, β-amyloid, liposome, mitogen-activated protein kinase

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Authors: Jia H. Wong, Jingli Zhang, Habsah Mohamad, Iswatun H. Abdullah Ripain, Muhammad Bilal, Amelia J. Lloyd, Abdul A. Mohamed Yusoff, Jafri M. Abdullah

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Epilepsy is one of the most common neurological diseases affecting more than 50 million of people worldwide. Epilepsy is a state of recurrent, spontaneous seizures with multiple syndromes and symptoms of different causes of brain dysfunction, prognosis, and treatments; characterized by transient, occasional and stereotyped interruptions of behavior whereby the excitatory-inhibitory activities within the central nervous system (CNS) are thrown out of balance due to various kinds of interferences. The goal of antiepileptic treatment is to enable patients to be free from seizures or to achieve control of seizures through surgical treatment and/or pharmacotherapy. Pharmacotherapy through AED plays an important role especially in countries with epilepsy treatment gap due to costs and availability of health facilities, skills and resources, yet there are about one-third of the people with epilepsy have drug-resistant seizures. Hence, this poses considerable challenges to the healthcare system and the effort in providing cost-effective treatment as well as the search for alternatives to treatment and management of epilepsy. Enhancement of γ-aminobutyric acid (GABA)-mediated inhibitory neurotransmission is one of the key mechanisms of actions of antiepileptic drugs. GABA type > a receptors (GABAAR) are ligand-gated ion channels that mediate rapid inhibitory neurotransmission upon the binding of GABA with a heteropentameric structure forming a central pore that is permeable to the influx of chloride ions in its activated state. The major isoform of GABAA receptors consists of two α1, two β2, and one γ2 subunit. It is the most abundantly expressed combinations in the brain and the most commonly researched through Xenopus laevis oocytes. With the advancing studies on ethnomedicine and traditional treatments using medicinal plants, increasing evidence reveal that spice and herb plants with medicinal properties play an important role in the treatment of ailments within communities across different cultures. Capsaicin is the primary natural capsaicinoid in hot peppers of plant genus Capsicum, consist of an aromatic ring, an amide linkage and a hydrophobic side chain. The study showed that capsaicins conferred neuroprotection in status epilepticus mouse models through anti-ictogenic, hypothermic, antioxidative, anti-inflammatory, and anti-apoptotic actions in a dose-dependent manner. In this study, five capsaicin derivatives were tested for their ability to increase the GABA-induced chloride current on α1β2γ2S of GABAAR expressed on Xenopus laevis oocytes using the method of two-microelectrode voltage clamp. Two of the capsaicin derivatives, IS5 (N-(4-hydroxy-3-methoxybenzyl)-3-methylbutyramide) and IS10 (N-(4-hydroxy-3-methoxybenzyl)-decanamide) at a concentration of 30µM were able to significantly increase the GABA-induced chloride current with p=0.002 and p=0.026 respectively. This study were able to show the enhancement effect of two capsaicin derivatives with moderate length of hydrocarbon chain on this receptor subtype, revealing the promising inhibitory activity of capsaicin derivatives through enhancement of GABA-induced chloride current and further investigations should be carried out to verify its antiepileptic effects in animal models.

Keywords: α1β2γ2 GABAA receptors, α1β2γ2S, antiepileptic, capsaicin derivatives, two-microelectrode voltage clamp, Xenopus laevis oocytes

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Authors: Yiqi Zhu, Jean Francois Trani, Rameez Ulhassan

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Extreme weather phenomena increased by 46% between 2007 and 2017 and have become more intense with the rise in global average temperatures. This increased intensity of climate variations often induces humanitarian crises and particularly affects vulnerable populations in low- and middle-income countries (LMICs). Expectant and lactating mothers are among the most vulnerable groups. Pakistan ranks 10th among the most affected countries by climate disasters. In 2022, monsoon floods submerged a third of the country, causing the loss of 1,500 lives. Approximately 650,000 expectant and lactating mothers faced systematic stress from climatic disasters. Our study used participatory methods to investigate the systematic impact of climatic disasters on maternal health. In March 2023, we conducted six Group Model Building (GMB) workshops with healthcare workers, fathers, and mothers separately in two of the most affected areas in Pakistan. This study was approved by the Islamic Relief Research Review Board. GMB workshops consist of three sessions. In the first session, participants discussed the factors that impact maternal health. After identifying the factors, they discussed the connections among them and explored the system structures that collectively impact maternal health. Based on the discussion, a causal loop diagram (CLD) was created. Finally, participants discussed action ideas that could improve the system to enhance maternal health. Based on our discussions and the causal loop diagram, we identified interconnected factors at the family, community, and policy levels. Mothers and children are directly impacted by three interrelated factors: food insecurity, unstable housing, and lack of income. These factors create a reinforcing cycle that negatively affects both mothers and newborns. After the flood, many mothers were unable to produce sufficient breastmilk due to their health status. Without breastmilk and sufficient food for complementary feeding, babies tend to get sick in damp and unhygienic environments resulting from temporary or unstable housing. When parents take care of sick children, they miss out on income-generating opportunities. At the community level, the lack of access to clean water and sanitation (WASH) and maternal healthcare further worsens the situation. Structural failures such as a lack of safety nets and programs associated with flood preparedness make families increasingly vulnerable with each disaster. Several families reported that they had not fully recovered from a flood that occurred ten years ago, and this latest disaster destroyed their lives again. Although over twenty non-profit organizations are working in these villages, few of them provide sustainable support. Therefore, participants called for systemic changes in response to the increasing frequency of climate disasters. The study reveals the systematic vulnerabilities of mothers and children after climatic disasters. The most vulnerable populations are often affected the most by climate change. Collaborative efforts are required to improve water and forest management, strengthen public infrastructure, increase access to WASH, and gradually build climate-resilient communities. Governments, non-governmental organizations, and the community should work together to develop and implement effective strategies to prevent, mitigate, and adapt to climate change and its impacts.

Keywords: climatic disasters, maternal health, Pakistan, systematic impact, flood, disaster relief.

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Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

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Authors: Aidan Ryan, Nahima Miah, Sahaj Kaur, Imogen Sutherland, Mohamed Saleh

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Pulmonary symptoms are a common presentation to the emergency department. Due to a lack of understanding of the underlying pathophysiology, chronic liver disease is not often considered a cause of dyspnea. We present three patients who were admitted with significant respiratory distress secondary to hepatopulmonary syndrome, portopulmonary hypertension, and hepatic hydrothorax. The first is a 27-year-old male with a 6-month history of progressive dyspnea. The patient developed a severe type 1 respiratory failure with a PaO₂ of 6.3kPa and was escalated to critical care, where he was managed with non-invasive ventilation to maintain oxygen saturation. He had an agitated saline contrast echocardiogram, which showed the presence of a possible shunt. A CT angiogram revealed significant liver cirrhosis, portal hypertension, and large para esophageal varices. Ultrasound of the abdomen showed coarse liver echo patter and enlarged spleen. Along with these imaging findings, his biochemistry demonstrated impaired synthetic liver function with an elevated international normalized ratio (INR) of 1.4 and hypoalbuminaemia of 28g/L. The patient was then transferred to a tertiary center for further management. Further investigations confirmed a shunt of 56%, and liver biopsy confirmed cirrhosis suggestive of alpha-1-antitripsyin deficiency. The findings were consistent with a diagnosis of hepatopulmonary syndrome, and the patient is awaiting a liver transplant. The second patient is a 56-year-old male with a 12-month history of worsening dyspnoea, jaundice, confusion. His medical history included liver cirrhosis, portal hypertension, and grade 1 oesophageal varices secondary to significant alcohol excess. On admission, he developed a type 1 respiratory failure with PaO₂ of 6.8kPa requiring 10L of oxygen. CT pulmonary angiogram was negative for pulmonary embolism but showed evidence of chronic pulmonary hypertension, liver cirrhosis, and portal hypertension. An echocardiogram revealed a grossly dilated right heart with reduced function, pulmonary and tricuspid regurgitation, and pulmonary artery pressures estimated at 78mmHg. His biochemical markers showed impaired synthetic liver function with an INR of 3.2, albumin of 29g/L, along with raised bilirubin of 148mg/dL. During his long admission, he was managed with diuretics with little improvement. After three weeks, he was diagnosed with portopulmonary hypertension and was commenced on terlipressin. This resulted in successfully weaning off oxygen, and he was discharged home. The third patient is a 61-year-old male who presented to the local ambulatory care unit for therapeutic paracentesis on a background of decompensated liver cirrhosis. On presenting, he complained of a 2-day history of worsening dyspnoea and a productive cough. Chest x-ray showed a large pleural effusion, increasing in size over the previous eight months, and his abdomen was visibly distended with ascitic fluid. Unfortunately, the patient deteriorated, developing a larger effusion along with an increase in oxygen demand, and passed away. Without underlying cardiorespiratory disease, in the presence of a persistent pleural effusion with underlying decompensated cirrhosis, he was diagnosed with hepatic hydrothorax. While each presented with dyspnoea, the cause and underlying pathophysiology differ significantly from case to case. By describing these complications, we hope to improve awareness and aid prompt and accurate diagnosis, vital for improving outcomes.

Keywords: dyspnea, hepatic hydrothorax, hepatopulmonary syndrome, portopulmonary syndrome

Procedia PDF Downloads 121

Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

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Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of a variety of bacterial infections. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi-drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. The present study analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, the range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin. According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Podoviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients. The findings of our research indicated that isolated phages could be an effective antimicrobial and an appreciate candidate for prophylaxis against pressure ulcers.

Keywords: acinetobacter baumannii, extremely drug-resistant, phage therapy, surgery wound

Procedia PDF Downloads 90

Authors: Jessica Ho

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AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

Procedia PDF Downloads 70

Authors: Leo Byrne, Neil Watts

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In the complex and evolving landscape of global trade, maritime sanctions emerge as a critical tool wielded by the international community to curb illegal activities and alter the behavior of non-compliant states and entities. These sanctions, designed to restrict or prohibit trade by sea with sanctioned jurisdictions, entities, or individuals, face continuous challenges due to the sophisticated evasion tactics employed by countries like North Korea. As the Democratic People's Republic of Korea (DPRK) diverts significant resources to circumvent these measures, understanding the nuances of their methodologies becomes imperative for maintaining the integrity of global trade systems. The DPRK, one of the most sanctioned nations globally, has developed an intricate network to facilitate its trade in illicit goods, ensuring the flow of revenue from designated activities continues unabated. Given its geographic and economic conditions, North Korea predominantly relies on maritime routes, utilizing foreign ports to route its illicit trade. This reliance on the sea is exploited through various sophisticated methods, including the use of front companies, falsification of documentation, commingling of bulk cargos, and physical alterations to vessels. These tactics enable the DPRK to navigate through the gaps in regulatory frameworks and lax oversight, effectively undermining international sanctions regimes Maritime sanctions carry significant implications for global trade, imposing heightened risks in the maritime domain. The deceptive practices employed not only by the DPRK but also by other high-risk jurisdictions, necessitate a comprehensive understanding of UN targeted sanctions. For stakeholders in the maritime sector—including maritime authorities, vessel owners, shipping companies, flag registries, and financial institutions serving the shipping industry—awareness and compliance are paramount. Violations can lead to severe consequences, including reputational damage, sanctions, hefty fines, and even imprisonment. To mitigate risks associated with these deceptive practices, it is crucial for maritime sector stakeholders to employ rigorous due diligence and regulatory compliance screening measures. Effective sanctions compliance serves as a protective shield against legal, financial, and reputational risks, preventing exploitation by international bad actors. This requires not only a deep understanding of the sanctions landscape but also the capability to identify and manage risks through informed decision-making and proactive risk management practices. As the DPRK and other sanctioned entities continue to evolve their sanctions evasion tactics, the international community must enhance its collective efforts to demystify and counter these practices. By leveraging more stringent compliance measures, stakeholders can safeguard against the illicit use of the maritime domain, reinforcing the effectiveness of maritime sanctions as a tool for global security. This paper seeks to dissect North Korea's adaptive strategies in the face of maritime sanctions. By examining up-to-date, geographically, and temporally relevant case studies, it aims to shed light on the primary nodes through which Pyongyang evades sanctions and smuggles goods via third-party ports. The goal is to propose multi-level interaction strategies, ranging from governmental interventions to localized enforcement mechanisms, to counteract these evasion tactics.

Keywords: maritime, maritime sanctions, international sanctions, compliance, risk

Procedia PDF Downloads 70

Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

Procedia PDF Downloads 171

Authors: Todd H. Buxton, Yong G. Lai

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Temperature management in regulated rivers can involve significant expenditures of water to meet the cold-water requirements of species in summer. For this purpose, flows released from Lewiston Dam on the Trinity River in Northern California are 12.7 cms with temperatures around 11oC in July through September to provide adult spring Chinook cold water to hold in deep pools and mature until spawning in fall. The releases are more than double the flow and 10oC colder temperatures than the natural conditions before the dam was built. The high, cold releases provide springers the habitat they require but may suppress the stream food base and limit future populations of salmon by reducing the juvenile fish size and survival to adults via the positive relationship between the two. Field and modeling research was undertaken to explore whether lowering summer releases from Lewiston Dam may promote thermal stratification in river pools so that both the cold-water needs of adult salmon and warmer water requirements of other organisms in the stream biome may be met. For this investigation, a three-dimensional (3D) computational fluid dynamics (CFD) model was developed and validated with field measurements in two deep pools on the Trinity River. Modeling and field observations were then used to identify the flows and temperatures that may form and maintain thermal stratification under different meteorologic conditions. Under low flows, a pool was found to be well mixed and thermally homogenous until temperatures began to stratify shortly after sunrise. Stratification then strengthened through the day until shading from trees and mountains cooled the inlet flow and decayed the thermal gradient, which collapsed shortly before sunset and returned the pool to a well-mixed state. This diurnal process of stratification formation and destruction was closely predicted by the 3D CFD model. Both the model and field observations indicate that thermal stratification maintained the coldest temperatures of the day at ≥2m depth in a pool and provided water that was around 8oC warmer in the upper 2m of the pool. Results further indicate that the stratified pool under low flows provided almost the same daily average temperatures as when flows were an order of magnitude higher and stratification was prevented, indicating significant water savings may be realized in regulated streams while also providing a diversity in water temperatures the ecosystem requires. With confidence in the 3D CFD model, the model is now being applied to a dozen pools in the Trinity River to understand how pool bathymetry influences thermal stratification under variable flows and diurnal temperature variations. This knowledge will be used to expand the results to 52 pools in a 64 km reach below Lewiston Dam that meet the depth criteria (≥2 m) for spring Chinook holding. From this, rating curves will be developed to relate discharge to the volume of pool habitat that provides springers the temperature (<15.6oC daily average), velocity (0.15 to 0.4 m/s) and depths that accommodate the escapement target for spring Chinook (6,000 adults) under maximum fish densities measured in other streams (3.1 m3/fish) during the holding time of year (May through August). Flow releases that meet these goals will be evaluated for water savings relative to the current flow regime and their influence on indicator species, including the Foothill Yellow-Legged Frog, and aspects of the stream biome that support salmon populations, including macroinvertebrate production and juvenile Chinook growth rates.

Keywords: 3D CFD modeling, flow regulation, thermal stratification, chinook salmon, foothill yellow-legged frogs, water managment

Procedia PDF Downloads 64

Authors: Ling Ai, Ziyu Zhao, Zeyu Zhou, Xiaochen Yang, Heng Zhai, Stuart Holmes

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Optimizing the catalyst layer structure is crucial for enhancing the performance of proton exchange membrane fuel cells (PEMFCs) with low Platinum (Pt) loading. Current works focused on the utilization, durability, and site activity of Pt particles on support, and performance enhancement has been achieved by loading Pt onto porous support with different morphology, such as graphene, carbon fiber, and carbon black. Some schemes have also incorporated cost considerations to achieve lower Pt loading. However, the design of the catalyst layer (CL) structure in the membrane electrode assembly (MEA) must consider the interactions between the layers. Addressing the crucial aspects of water management, low contact resistance, and the establishment of effective three-phase boundary for MEA, multi-walled carbon nanotubes (MWCNTs) are promising CL support due to their intrinsically high hydrophobicity, high axial electrical conductivity, and potential for ordered alignment. However, the drawbacks of MWCNTs, such as strong agglomeration, wall surface chemical inertness, and unopened ends, are unfavorable for Pt nanoparticle loading, which is detrimental to MEA processing and leads to inhomogeneous CL surfaces. This further deteriorates the utilization of Pt and increases the contact resistance. Robust chemical oxidation or nitrogen doping can introduce polar functional groups onto the surface of MWCNTs, facilitating the creation of open tube ends and inducing defects in tube walls. This improves dispersibility and load capacity but reduces length and conductivity. Consequently, a trade-off exists between maintaining the intrinsic properties and the degree of functionalization of MWCNTs. In this work, MWCNTs were modified based on the operational requirements of the MEA from the viewpoint of interlayer interactions, including the search for the optimal degree of oxidation, N-doping, and micro-arrangement. MWCNT were functionalized by oxidizing, N-doping, as well as micro-alignment to achieve lower contact resistance between CL and proton exchange membrane (PEM), better hydrophobicity, and enhanced performance. Furthermore, this work expects to construct a more continuously distributed three-phase boundary by aligning MWCNT to form a locally ordered structure, which is essential for the efficient utilization of Pt active sites. Different from other chemical oxidation schemes that used HNO3:H2SO4 (1:3) mixed acid to strongly oxidize MWCNT, this scheme adopted pure HNO3 to partially oxidize MWCNT at a lower reflux temperature (80 ℃) and a shorter treatment time (0 to 10 h) to preserve the morphology and intrinsic conductivity of MWCNT. The maximum power density of 979.81 mw cm-2 was achieved by Pt loading on 6h MWCNT oxidation time (Pt-MWCNT6h). This represented a 59.53% improvement over the commercial Pt/C catalyst of 614.17 (mw cm-2). In addition, due to the stronger electrical conductivity, the charge transfer resistance of Pt-MWCNT6h in the electrochemical impedance spectroscopy (EIS) test was 0.09 Ohm cm-2, which was 48.86% lower than that of Pt/C. This study will discuss the developed catalysts and their efficacy in a working fuel cell system. This research will validate the impact of low-functionalization modification of MWCNTs on the performance of PEMFC, which simplifies the preparation challenges of CL and contributing for the widespread commercial application of PEMFCs on a larger scale.

Keywords: carbon nanotubes, electrocatalyst, membrane electrode assembly, proton exchange membrane fuel cell

Procedia PDF Downloads 69

Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

Procedia PDF Downloads 127

Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

Procedia PDF Downloads 41

Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

Procedia PDF Downloads 160

Authors: Ananya Pappu, Sneha Mishra

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Introduction: The South Asian population experiences unique health challenges that predisposes this demographic to cardiometabolic diseases at lower BMIs. South Asians may therefore benefit from recommendations specific to their cultural needs. Here, we focus on current BMI guidelines for Asians with a discussion of South Asian dietary practices and culturally tailored interventions. By integrating traditional dietary practices with modern nutritional recommendations, this manuscript aims to highlight effective strategies to improving health outcomes among South Asians. Background: The South Asian community, including individuals from India, Pakistan, Bangladesh, and Sri Lanka, experiences high rates of cardiovascular diseases, cancers, diabetes, and strokes. Notably, the prevalence of diabetes and cardiovascular disease among Asians is elevated at BMIs below the WHO's standard overweight threshold. As it stands, a BMI of 25-30 kg/m² is considered overweight in non-Asians, while this cutoff is reduced to 23-27.4 kg/m² in Asians. This discrepancy can be attributed to studies which have shown different associations between BMI and health risks in Asians compared to other populations. Given these significant challenges, optimizing lifestyle management for cardiometabolic risk factors is crucial. Tailored interventions that consider cultural context seem to be the best approach for ensuring the success of both dietary and physical activity interventions in South Asian patients. Adopting a whole food, plant-based diet (WFPD) is one such strategy. The WFPD suggests that half of one meal should consist of non-starchy vegetables. In the South Asian diet, this includes traditional vegetables such as okra, tindora, eggplant, and leafy greens including amaranth, collards, chard, and mustards. A quarter of the meal should include plant-based protein sources like cooked beans, lentils, and paneer, with the remaining quarter comprising healthy grains or starches such as whole wheat breads, millets, tapioca, and barley. Adherence to the WFPD has been shown to improve cardiometabolic risk factors including weight, BMI, total cholesterol, HbA1c, and reduces the risk of developing non-alcoholic fatty liver disease (NAFLD). Another approach to improving dietary habits is timing meals. Many of the major cultures and religions in the Indian subcontinent incorporate religious fasting. Time-restricted eating (TRE), also known as intermittent fasting, is a practice akin to traditional fasting, which involves consuming all daily calories within a specific window. TRE has been shown to improve insulin resistance in prediabetic and diabetic patients. Common regimens include completing all meals within an 8-hour window, consuming a low-calorie diet every other day, and the 5:2 diet, which involves fasting twice weekly. These fasting practices align with the natural circadian rhythm, potentially enhancing metabolic health and reducing obesity and diabetes risks. Conclusion: South Asians develop cardiometabolic disease at lower BMIs; hence, it is important to counsel patients about lifestyle interventions that decrease their risk. Traditional South Asian diets can be made more nutrient-rich by incorporating vegetables, plant proteins like lentils and beans, and substituting refined grains for whole grains. Ultimately, the best diet is one to which a patient can adhere. It is therefore important to find a regimen that aligns with a patient’s cultural and traditional food practices.

Keywords: BMI, diet, obesity, South Asian, time-restricted eating

Procedia PDF Downloads 44

Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

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Authors: Sitira Williams, Georgina Cherry, Andrea Wright, Kevin Wells, Taran Rai, Richard Brown, Travis Street, Alasdair Cook

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Social media sources (50) were identified, keywords defined by veterinarians and organised into 6 topics known to be indicative of feline pruritus: body areas, behaviors, symptoms, diagnosis, and treatments. These were augmented using academic literature, a cat owner survey, synonyms, and Google Trends. The content was collected using a social intelligence solution, with keywords tagged and filtered. Data were aggregated and de-duplicated. SL content matching body areas, behaviors and symptoms were reviewed manually, and posts were marked relevant if: posted by a pet owner, identifying an itchy cat and not duplicated. A sub-set of 493 posts published from 2009-2022 was used for reflexive thematic analysis in NVIVO (Burlington, MA) to identify themes. Five themes were identified: allergy, pruritus, additional behaviors, unusual or undesirable behaviors, diagnosis, and treatment. Most (258) posts reported the cat was excessively licking, itching, and scratching. The majority were indoor cats and were less playful and friendly when itchy. Half of these posts did not indicate a known cause of pruritus. Bald spots and scabs (123) were reported, often causing swelling and fur loss, and 56 reported bumps, lumps, and dry patches. Other impacts on the cat’s quality of life were ear mites, cat self-trauma and stress. Seven posts reported their cats’ symptoms caused them ongoing anxiety and depression. Cats with food allergies to poultry (often chicken and beef) causing bald spots featured in 23 posts. Veterinarians advised switching to a raw food diet and/or changing their bowls. Some cats got worse after switching, leaving owners’ needs unmet. Allergic reactions to flea bites causing excessive itching, red spots, scabs, and fur loss were reported in 13 posts. Some (3) posts indicated allergic reactions to medication. Cats with seasonal and skin allergies, causing sneezing, scratching, headshaking, watery eyes, and nasal discharge, were reported 17 times. Eighty-five posts identified additional behaviors. Of these, 13 reported their cat’s burst pimple or insect bite. Common behaviors were headshaking, rubbing, pawing at their ears, and aggressively chewing. In some cases, bites or pimples triggered previously unseen itchiness, making the cat irritable. Twenty-four reported their cat had anxiety: overgrooming, itching, losing fur, hiding, freaking out, breathing quickly, sleeplessness, hissing and vocalising. Most reported these cats as having itchy skin, fleas, and bumps. Cats were commonly diagnosed with an ear infection, ringworm, acne, or kidney disease. Acne was diagnosed in cats with an allergy flare-up or overgrooming. Ear infections were diagnosed in itchy cats with mites or other parasites. Of the treatments mentioned, steroids were most frequently used, then anti-parasitics, including flea treatments and oral medication (steroids, antibiotics). Forty-six posts reported distress following poor outcomes after medication or additional vet consultations. SL provides veterinarians with unique insights. Verbatim comments highlight the detrimental effects of pruritus on pets and owner quality of life. This study demonstrates the need for veterinarians to communicate management and treatment options more effectively to relieve owner frustrations. Data analysis could be scaled up using machine learning for topic modeling.

Keywords: content analysis, feline, itch, pruritus, social media, thematic analysis, veterinary dermatology

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Authors: Priyanka Botny Srinath, Alessandro Suglia, Mel McKendrick

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Background: Organizational cultural studies integrate sociology and anthropology, portraying man as a creator of symbols, languages, beliefs, and ideologies -essentially, a creator and manager of meaning. In our research, we leverage analytical measures to discern whether an organization embodies a singular culture or a myriad of subcultures. Fast-forward to 2023, our research thesis focuses on digitally measuring culture, coining it as the "Work Culture Quotient." This entails conceptually mapping common experiential patterns to provide executives insights into the digital organization journey, aiding in understanding their current position and identifying future steps. Objectives: Finding the new age skills that help in defining the culture; understand the implications of post-COVID effects; derive a digital framework for measuring skillsets. Method: We conducted two comprehensive Delphi studies to distill essential insights. Delphi 1: Through a thematic analysis of interviews with 20 high-level leaders representing companies across diverse regions -India, Japan, the US, Canada, Morocco, and Uganda- we identified 20 key skills critical for cultivating a robust organizational culture. The skills are -influence, self-confidence, optimism, empathy, leadership, collaboration and cooperation, developing others, commitment, innovativeness, leveraging diversity, change management, team capabilities, self-control, digital communication, emotional awareness, team bonding, communication, problem solving, adaptability, and trustworthiness. Delphi 2: Subject matter experts were asked to complete a questionnaire derived from the thematic analysis in stage 1 to formalise themes and draw consensus amongst experts on the most important workplace skills. Results: The thematic analysis resulted in 20 workplace employee skills being identified. These skills were all included in the Delphi round 2 questionnaire. From the outputs, we analysed the data using R Studio for arriving at agreement and consensus, we also used sum of squares method to compare various agreements to extract various themes with a threshold of 80% agreements. This yielded three themes at over 80% agreement (leadership, collaboration and cooperation, communication) and three further themes at over 60% agreement (commitment, empathy, trustworthiness). From this, we selected five questionnaires to be included in the primary data collection phase, and these will be paired with the digital footprints to provide a workplace culture quotient. Implications: The findings from these studies bear profound implications for decision-makers, revolutionizing their comprehension of organizational culture. Tackling the challenge of mapping the digital organization journey involves innovative methodologies that probe not only external landscapes but also internal cultural dynamics. This holistic approach furnishes decision-makers with a nuanced understanding of their organizational culture and visualizes pivotal skills for employee growth. This clarity enables informed choices resonating with the organization's unique cultural fabric. Anticipated outcomes transcend mere individual cultural measurements, aligning with organizational goals to unveil a comprehensive view of culture, exposing artifacts and depth. Armed with this profound understanding, decision-makers gain tangible evidence for informed decision-making, strategically leveraging cultural strengths to cultivate an environment conducive to growth, innovation, and enduring success, ultimately leading to measurable outcomes.

Keywords: leadership, cooperation, collaboration, teamwork, work culture

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Authors: Shari S. C. Shang, Lynn S. L. Chiu

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In the digital payment market, some consumers use only one payment wallet while many others play multi-homing with a variety of payment services. With the diffusion of new payment systems, we examined the determinants of the adoption of multi-homing behavior. This study aims to understand how a digital payment provider dynamically expands business touch points with cross-business strategies to enrich the digital ecosystem and avoid the trap of multi-homing in customers. By synthesizing platform ecosystem literature, we constructed a two-dimensional research framework with one determinant of user digital behavior from offline to online intentions and the other determinant of digital payment touch points from convenient accessibility to cross-business platforms. To explore on a broader scale, we selected 12 digital payments from 5 countries of UK, US, Japan, Korea, and Taiwan. With the interplays of user digital behaviors and payment touch points, we group the study cases into four types: (1) Channel Initiated: users originated from retailers with high access to in-store shopping with face-to-face guidance for payment adoption. Providers offer rewards for customer loyalty and secure the retailer’s efficient cash flow management. (2) Social Media Dependent: users usually are digital natives with high access to social media or the internet who shop and pay digitally. Providers might not own physical or online shops but are licensed to aggregate money flows through virtual ecosystems. (3) Early Life Engagement: digital banks race to capture the next generation from popularity to profitability. This type of payment aimed to give children a taste of financial freedom while letting parents track their spending. Providers are to capitalize on the digital payment and e-commerce boom and hold on to new customers into adulthood. (4) Traditional Banking: plastic credit cards are purposely designed as a control group to track the evolvement of business strategies in digital payments. Traditional credit card users may follow the bank’s digital strategy to land on different types of digital wallets or mostly keep using plastic credit cards. This research analyzed business growth models and inter-firms’ coopetition strategies of the selected cases. Results of the multiple case analysis reveal that channel initiated payments bundled rewards with retailer’s business discount for recurring purchases. They also extended other financial services, such as insurance, to fulfill customers’ new demands. Contrastively, social media dependent payments developed new usages and new value creation, such as P2P money transfer through network effects among the virtual social ties, while early life engagements offer virtual banking products to children who are digital natives but overlooked by incumbents. It has disrupted the banking business domains in preparation for the metaverse economy. Lastly, the control group of traditional plastic credit cards has gradually converted to a BaaS (banking as a service) model depending on customers’ preferences. The multi-homing behavior is not avoidable in digital payment competitions. Payment providers may encounter multiple waves of a multi-homing threat after a short period of success. A dynamic cross-business collaboration strategy should be explored to continuously evolve the digital ecosystems and allow users for a broader shopping experience and continual usage.

Keywords: digital payment, digital ecosystems, multihoming users, cross business strategy, user digital behavior intentions

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Authors: Nino Kupatadze, Tamar Memanishvili, Natia Ochkhikidze, David Tugushi, Zaal Kokaia, Ramaz Katsarava

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Amino acid-based Biodegradable poly(ester-amide)s (PEAs) have gained considerable interest as a promising materials for numerous biomedical applications. These polymers reveal a high biocompatibility and easily form small particles suitable for delivery various biological, as well as elastic bio-erodible films serving as matrices for constructing antibacterial coatings. In the present work we have demonstrated a potential of the PEAs for two applications: 1. cell therapy for stroke as vehicles for delivery and sustained release of growth factors, 2. bactericidal coating as prevention biofilm and applicable in infected wound management. Stroke remains the main cause of adult disability with limited treatment options. Although stem cell therapy is a promising strategy, it still requires improvement of cell survival, differentiation and tissue modulation. .Recently, microspheres (MPs) made of biodegradable polymers have gained significant attention for providing necessary support of transplanted cells. To investigate this strategy in the cell therapy of stroke, MPs loaded with transcription factors Wnt3A/BMP4 were prepared. These proteins have been shown to mediate the maturation of the cortical neurons. We have suggested that implantation of these materials could create a suitable microenvironment for implanted cells. Particles with spherical shape, porous surface, and 5-40 m in size (monitored by scanning electron microscopy) were made on the basis of the original PEA composed of adipic acid, L-phenylalanine and 1,4-butanediol. After 4 months transplantation of MPs in rodent brain, no inflammation was observed. Additionally, factors were successfully released from MPs and affected neuronal cell differentiation in in vitro. The in vivo study using loaded MPs is in progress. Another severe problem in biomedicine is prevention of surgical devices from biofilm formation. Antimicrobial polymeric coatings are most effective “shields” to protect surfaces/devices from biofilm formation. Among matrices for constructing the coatings preference should be given to bio-erodible polymers. Such types of coatings will play a role of “unstable seating” that will not allow bacteria to occupy the surface. In other words, bio-erodible coatings would be discomfort shelter for bacteria that along with releasing “killers of bacteria” should prevent the formation of biofilm. For this purpose, we selected an original biodegradable PEA composed of L-leucine, 1,6-hexanediol and sebacic acid as a bio-erodible matrix, and nanosilver (AgNPs) as a bactericidal agent (“killer of bacteria”). Such nanocomposite material is also promising in treatment of superficial wound and ulcer. The solubility of the PEA in ethanol allows to reduce AgNO3 to NPs directly in the solution, where the solvent served as a reductive agent, and the PEA served as NPs stabilizer. The photochemical reduction was selected as a basic method to form NPs. The obtained AgNPs were characterized by UV-spectroscopy, transmission electron microscope (TEM), and dynamic light scattering (DLS). According to the UV-data and TEM data the photochemical reduction resulted in spherical AgNPs with wide particle size distribution with a high contribution of the particles below 10 nm that are known as responsible for bactericidal activity of AgNPs. DLS study showed that average size of nanoparticles formed after photo-reduction in ethanol solution ranged within ca. 50 nm.

Keywords: biodegradable polymers, microparticles, nanocomposites, stem cell therapy, stroke

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Authors: Yimer Mohammed Assen, Abiyot Legesse Kura, Engida Esyas Dube, Asebe Regassa Debelo, Girma Kelboro Mensuro, Lete Bekele Gure

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Climate change has posed severe threats to many cultural landscapes of UNESCO world heritage sites recently. The UNESCO State of Conservation (SOC) reports categorized flooding, temperature increment, and drought as threats to cultural landscapes. This study aimed to examine variations and trends of rainfall and temperature extreme events and their threats to the UNESCO-designated Konso Cultural Landscape in southern Ethiopia. The study used dense merged satellite-gauge station rainfall data (1981-2020) with spatial resolution of 4km by 4km and observed maximum and minimum temperature data (1987-2020). Qualitative data were also gathered from cultural leaders, local administrators, and religious leaders using structured interview checklists. The spatial patterns, coefficient of variation, standardized anomalies, trends, and magnitude of change of rainfall and temperature extreme events both at annual and seasonal levels were computed using the Mann-Kendall trend test and Sen’s slope estimator under the CDT package. The standard precipitation index (SPI) was also used to calculate drought severity, frequency, and trend maps. The data gathered from key informant interviews and focus group discussions were coded and analyzed thematically to complement statistical findings. Thematic areas that explain the impacts of extreme events on the cultural landscape were chosen for coding. The thematic analysis was conducted using Nvivo software. The findings revealed that rainfall was highly variable and unpredictable, resulting in extreme drought and flood. There were significant (P<0.05) increasing trends of heavy rainfall (R10mm and R20mm) and the total amount of rain on wet days (PRCPTOT), which might have resulted in flooding. The study also confirmed that absolute temperature extreme indices (TXx, TXn, and TNx) and the percentile-based temperature extreme indices (TX90p, TN90p, TX10p, and TN10P) showed significant (P<0.05) increasing trends which are signals for warming of the study area. The results revealed that the frequency as well as the severity of drought at 3-months (katana/hageya seasons) was more pronounced than the 12-months (annual) time scale. The highest number of droughts in 100 years is projected at a 3-months timescale across the study area. The findings also showed that frequent drought has led to loss of grasses which are used for making traditional individual houses and multipurpose communal houses (pafta), food insecurity, migration, loss of biodiversity, and commodification of stones from terrace. On the other hand, the increasing trends of rainfall extreme indices resulted in destruction of terraces, soil erosion, loss of life and damage of properties. The study shows that a persistent decline in farmland productivity, due to erratic and extreme rainfall and frequent drought occurrences, forced the local people to participate in non-farm activities and retreat from daily preservation and management of their landscape. Overall, the increasing rainfall and temperature extremes coupled with prevalence of drought are thought to have an impact on the sustainability of cultural landscape through disrupting the ecosystem services and livelihood of the community. Therefore, more localized adaptation and mitigation strategies to the changing climate are needed to maintain the sustainability of Konso cultural landscapes as a global cultural treasure and to strengthen the resilience of smallholder farmers.

Keywords: adaptation, cultural landscape, drought, extremes indices

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Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Shuhui Gong, Limei Tang, Ruoliang Tang

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Introduction: Healthcare workers, especially the nurses all over the world, are highly vulnerable to work-related musculoskeletal disorders (WMSDs), experiencing high rates of neck, shoulder, and low back injuries, due to the unfavorable working conditions. To reduce WMSDs among nursing personnel, many workplace interventions have been developed and implemented. Unfortunately, the ongoing Covid-19 (SARS-CoV-2) pandemic has posed great challenges to the ergonomic practices and interventions in healthcare facilities, particularly the hospitals, since current Covid-19 mitigation measures, such as social distancing and working remotely, has substantially minimized in-person gatherings and trainings. On the other hand, hospitals throughout the world have been short-staffed, resulting in disturbance of shift scheduling and more importantly, the increased job demand among the available caregivers, particularly the doctors and nurses. With the latest development in communication technology, remote intervention measures have been developed as an alternative, without the necessity of in-person meetings. The Omaha System (OS) is a standardized classification system for nursing practices, including a problem classification system, an intervention system, and an outcome evaluation system. This paper describes the development of an OS-based ergonomic intervention program. Methods: First, a comprehensive literature search was performed among worldwide electronic databases, including PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), between journal inception to May 2020, resulting in a total of 1,418 scientific articles. After two independent screening processes, the final knowledge pool included eleven randomized controlled trial studies to develop the draft of the intervention program with Omaha intervention subsystem as the framework. After the determination of sample size needed for statistical power and the potential loss to follow-up, a total of 94 nurses from eight clinical departments agreed to provide written, informed consent to participate in the study, which were subsequently assigned into two random groups (i.e., intervention vs. control). A subgroup of twelve nurses were randomly selected to participate in a semi-structured interview, during which their general understanding and awareness of musculoskeletal disorders and potential interventions was assessed. Then, the first draft was modified to reflect the findings from these interviews. Meanwhile, the tentative program schedule was also assessed. Next, two rounds of consultation were conducted among experts in nursing management, occupational health, psychology, and rehabilitation, to further adjust and finalize the intervention program. The control group had access to all the information and exercise modules at baseline, while an interdisciplinary research team was formed and supervised the implementation of the on-line intervention program through multiple social media groups. Outcome measures of this comparative study included biomechanical load assessed by the Quick Exposure Check and stresses due to awkward body postures. Results and Discussion: Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, and (3) revising the on-line training method. Information module should be once a week, lasting about 20 to 30 minutes, for a total of 6 weeks, while the exercise module should be 5 times a week, each lasting about 15 to 20 minutes, for a total of 6 weeks.

Keywords: ergonomic interventions, musculoskeletal disorders (MSDs), omaha system, nurses, Covid-19

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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