Search results for: squared prediction risk

Authors: Ilija Kelepurovski, Stefan Lazorovski, Pece Petkovski, Marian Anakievski, Svetlana Petkovska

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Introduction: Benign prostatic hyperplasia (BPH) is a common condition that affects men over the age of 50 and is characterized by an enlarged prostate gland that can cause lower urinary tract symptoms (LUTS). Uroflowmetry and cystoscopy are two commonly used diagnostic tests to evaluate LUTS and diagnose BPH. While both tests can be useful, there is a risk of overusing cystoscopy and underusing uroflowmetry in the evaluation of LUTS. The aim of this study was to compare the use of uroflowmetry and cystoscopy in a prospective cohort of 100 patients with suspected BPH or other urinary tract conditions and to assess the diagnostic yield of each test. Materials and Methods: This was a prospective study of 100 male patients over the age of 50 with suspected BPH or other urinary tract conditions who underwent uroflowmetry and cystoscopy for the evaluation of LUTS at a single tertiary care center. Inclusion criteria included male patients over the age of 50 with suspected BPH or other urinary tract conditions, while exclusion criteria included previous urethral or bladder surgery, active urinary tract infection, and significant comorbidities. The primary outcome of the study was the frequency of cystoscopy in the evaluation of LUTS, and the secondary outcome was the diagnostic yield of each test. Results: Of the 100 patients included in the study, 86 (86%) were diagnosed with BPH and 14 (14%) had other urinary tract conditions. The mean age of the study population was 67 years. Uroflowmetry was performed on all 100 patients, while cystoscopy was performed on 70 (70%) of the patients. The diagnostic yield of uroflowmetry was high, with a clear diagnosis made in 92 (92%) of the patients. The diagnostic yield of cystoscopy was also high, with a clear diagnosis made in 63 (90%) of the patients who underwent the procedure. There was no statistically significant difference in the diagnostic yield of uroflowmetry and cystoscopy (p = 0.20). Discussion: Our study found that uroflowmetry is an effective and well-tolerated diagnostic tool for evaluating LUTS and diagnosing BPH, with a high diagnostic yield and low risk of complications. Cystoscopy is also a useful diagnostic tool, but it is more invasive and carries a small risk of complications such as bleeding or urinary tract infection. Both tests had a high diagnostic yield, suggesting that either test can provide useful information in the evaluation of LUTS. However, the fact that 70% of the study population underwent cystoscopy raises concerns about the potential overuse of this test in the evaluation of LUTS. This is especially relevant given the focus on patient-centered care and the need to minimize unnecessary or invasive procedures. Our findings underscore the importance of considering the clinical context and using evidence-based guidelines. Conclusion: In this prospective study of 100 patients with suspected BPH or other urinary tract conditions, we found that uroflowmetry and cystoscopy were both valuable diagnostic tools for the evaluation of LUTS. However, the potential overuse of cystoscopy in this population warrants further investigation and highlights the need for careful consideration of the optimal use of diagnostic tests in the evaluation of LUTS and the diagnosis of BPH. Further research is needed to better understand the relative roles of uroflowmetry and cystoscopy in the diagnostic workup of patients with LUTS, and to develop evidence-based guidelines for their appropriate use.

Keywords: uroflowmetry, cystoscopy, LUTS, BPH

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Authors: Yu-Yao Wang, Xiao-Meng Hu, Joanne Yeung, Xiao-Yan Li

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The high private cost and unquantified external cost limit the development of reclaimed water. In this study, an integrated framework comprising life cycle assessment (LCA), quantitative microbial risk assessment (QMRA), and life cycle costing (LCC) was developed to evaluate both costs of reclaimed water supply in water systems of various scales. LCA assesses the environmental impacts, and QMRA estimates the associated pathogenic impacts. These impacts are monetized as external costs and analyzed with the private cost by LCC to count the total life cycle cost. The framework evaluated the Hong Kong urban water system in the baseline scenario (BS) and five wastewater reuse scenarios (RS). They are RSI: substituting freshwater for toilet flushing only, RSII: substituting both freshwater and seawater for toilet flushing, RSIII: using reclaimed water for all non-potable uses, RSIV: using reclaimed water for all non-potable uses and indirect potable uses, and RSV: non-potable use and indirect potable use by conveying 100% reclaimed water to recharge the reservoirs. The results show that substituting freshwater and seawater for toilet flushing has the least total life cycle cost, exhibiting that it is the most cost-effective option for Hong Kong. Meanwhile, the evaluation results show that the external cost of each scenario is comparable to the corresponding private cost, indicating the importance of the inclusion of comprehensive external cost evaluation in private cost assessment of water systems with reclaimed water supply.

Keywords: life cycle assessment, life cycle costing, quantitative microbial risk assessment, water reclamation, reclaimed water, alternative water resources

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Authors: Sireen Irsheid

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Despite concerted efforts to improve education attainment with progress in recent years, student achievement and attainment remain among the most significant challenges for school districts across the United States. Many scholars have argued that students who do not complete high school do not drop out of school voluntarily but are ‘pushed out’ of schools through multiple mechanisms related to structural and socioeconomic barriers, behavioral health challenges, pedagogical practices, and administrative procedures. Extant literature has shown that living in historically disadvantaged neighborhoods or attending under-resourced schools exacerbates student-level risk factors for grade retention and school pushout. Most efforts to respond to the school pushout phenomenon have focused on individual characteristics of students, with relatively little attention to addressing these multiple system-level characteristics related to perpetuating inequities. This study is built on a growing body of social justice-oriented research concerned with the systemic influences that shape the experiences and mental health challenges of young people. Specifically, this study examined how young people who have been experiencing education inequities make meaning and navigate the structural factors related to neighborhood and school disinvestment and access to resources and supports, and their risk for school pushout. Furthermore, schools as political, cultural, and ideologically reproductive spaces often serve as sites of resistance and can support students who are impacted by educational inequity. Study findings provide education, neighborhood, school psychology, social work practice, and policy considerations.

Keywords: education policy, mental health, school prison nexus, school pushout, structural trauma

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Authors: E. O. Clarke, O. J. Aderinola, O. A. Adeboyejo, M. A. Anetekhai

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Aims: The study is aimed at establishing the influence of some physical and chemical parameters on the abundance, distribution pattern and seasonal variations of the planktonic crustacean populations. Place and Duration of Study: A premier investigation into the dynamics of planktonic crustacean populations in Ologe lagoon was carried out from January 2011 to December 2012. Study Design: The study covered identification, temporal abundance, spatial distribution and diversity of the planktonic crustacea. Methodology: Standard techniques were used to collect samples from eleven stations covering five proximal satellite towns (Idoluwo, Oto, Ibiye, Obele, and Gbanko) bordering the lagoon. Data obtained were statistically analyzed using linear regression and hierarchical clustering. Results:Thirteen (13) planktonic crustacean populations were identified. Total percentage abundance was highest for Bosmina species (20%) and lowest for Polyphemus species (0.8%). The Pearson’s correlation coefficient (“r” values) between total planktonic crustacean population and some physical and chemical parameters showed that positive correlations having low level of significance occurred with salinity (r = 0.042) (sig = 0.184) and with surface water dissolved oxygen (r = 0.299) (sig = 0.155). Linear regression plots indicated that, the total population of planktonic crustacea were mainly influenced and only increased with an increase in value of surface water temperature (Rsq = 0.791) and conductivity (Rsq = 0.589). The total population of planktonic crustacea had a near neutral (zero correlation) with the surface water dissolved oxygen and thus, does not significantly change with the level of the surface water dissolved oxygen. The correlations were positive with NO3-N (midstream) at Ibiye (Rsq =0.022) and (downstream) Gbanko (Rsq =0.013), PO4-P at Ibiye (Rsq =0.258), K at Idoluwo (Rsq =0.295) and SO4-S at Oto (Rsq = 0.094) and Gbanko (Rsq = 0.457). The Berger-Parker Dominance Index (BPDI) showed that the most dominant species was Bosmina species (BPDI = 1.000), followed by Calanus species (BPDI = 1.254). Clusters by squared Euclidan distances using average linkage between groups showed proximities, transcending the borders of genera. Conclusion: The results revealed that planktonic crustacean population in Ologe lagoon undergo seasonal perturbations, were highly influenced by nutrient, metal and organic matter inputs from river Owoh, Agbara industrial estate and surrounding farmlands and were patchy in spatial distribution.

Keywords: diversity, dominance, perturbations, richness, crustacea, lagoon

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Ena Arora, Rong Fan, Aleksandr Fuks, Kolawole Felix Akinnawonu

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Introduction: Leiomyomas are benign tumors that are derived from the overgrowth of uterine smooth muscle cells. Women with symptomatic leiomyomas who desire future fertility, myomectomy should be the standard surgical treatment. Perioperative hemorrhage is a common complication in myomectomy. We performed the study to investigate blood transfusion rate in abdominal myomectomies, risk factors influencing blood loss and modalities to improve perioperative blood loss. Methods: Retrospective chart review was done for patients who underwent myomectomy from 2016 to 2022 at Queens hospital center, New York. We looked at preoperative patient demographics, clinical characteristics, intraoperative variables, and postoperative outcomes. Mann-Whitney U test were used for parametric and non-parametric continuous variable comparisons, respectively. Results: A total of 159 myomectomies were performed between 2016 and 2022, including 1 laparoscopic, 65 vaginal and 93 abdominal. 44 patients received blood transfusion during or within 72 hours of abdominal myomectomy. The blood transfusion rate was 47.3%. Blood transfusion rate was found to be twice higher than the average documented rate in literature which is 20%. Risk factors identified were black race, preoperative hematocrit<30%, preoperative blood transfusion within 72 hours, large fibroid burden, prolonged surgical time, and abdominal approach. Conclusion: Preoperative optimization with iron supplements or GnRH agonists is important for patients undergoing myomectomy. Interventions to decrease intra operative blood loss should include cell saver, tourniquet, vasopressin, misoprostol, tranexamic acid and gelatin-thrombin matrix hemostatic sealant.

Keywords: myomectomy, perioperative blood loss, cell saver, tranexamic acid

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Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

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Authors: Lamia Bouzgarrou, Irtyah Merchaoui, Amira Omrane, Salma Kammoun, Amine Daafa, Neila Chaari

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Backgrounds: Currently, low back pain (LBP) is one of the most prevalent public health problems, which caused severe morbidity among a large portion of the adult population. It is also associated with heavy direct and indirect costs, in particular, related to absenteeism and early retirement. Health care workers are one of most occupational groups concerned by LBP, especially because of biomechanical and psycho-organizational risk factors. Our current study aims to investigate risk factors associated with chronic low back pain among Tunisian caregivers in university-hospitals. Methods: Cross-sectional study conducted over a period of 14 months, with a representative sample of caregivers, matched according to age, sex and work department, in two university-hospitals in Tunisia. Data collection included items related to socio-professional characteristics, the evaluation of the working capacity index (WAI), the occupational stress (Karazek job strain questionnaire); the quality of life (SF12), the musculoskeletal disorders Nordic questionnaire, and the examination of the spine flexibility (distance finger-ground, sit-stand maneuver and equilibrium test). Results: Totally, 293 caregivers were included with a mean age equal to 42.64 ± 11.65 years. A body mass index (BMI) exceeding 30, was noted in 20.82% of cases. Moreover, no regular physical activity was practiced in 51.9% of cases. In contrast, domestic activity equal or exceeding 20 hours per week, was reported by 38.22%. Job strain was noted in 19.79 % of cases and the work capacity was 'low' to 'average' among 27.64% of subjects. During the 12 months previous to the investigation, 65% of caregivers complained of LBP, with pain rated as 'severe' or 'extremely severe' in 54.4% of cases and with a frequency of discomfort exceeding one episode per week in 58.52% of cases. During physical examination, the mean distance finger-ground was 7.10 ± 7.5cm. Caregivers assigned to 'high workload' services had the highest prevalence of LBP (77.4%) compared to other categories of hospital services, with no statistically significant relationship (P = 0.125). LBP prevalence was statistically correlated with female gender (p = 0.01) and impaired work capacity (p < 10⁻³). Moreover, the increase of the distance finger-ground was statistically associated with LBP (p = 0.05), advanced age (p < 10⁻³), professional seniority (p < 10⁻³) and the BMI ≥ 25 (p = 0.001). Furthermore, others physical tests of spine flexibility were underperformed among LBP suffering workers with a statistically significant difference (sit-stand maneuver (p = 0.03); equilibrium test (p = 0.01)). According to the multivariate analysis, only the domestic activity exceeding 20H/week, the degraded quality of physical life, and the presence of neck pain were significantly corelated to LBP. The final model explains 36.7% of the variability of this complaint. Conclusion: Our results highlighted the elevate prevalence of LBP among caregivers in Tunisian public hospital and identified both professional and individual predisposing factors. The preliminary analysis supports the necessity of a multidimensional approach to prevent this critical occupational and public health problem. The preventive strategy should be based both on the improvement of working conditions, and also on lifestyle modifications, and reinforcement of healthy behaviors in these active populations.

Keywords: health care workers, low back pain, prevention, risk factor

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Catelyn Coyle, Helena Kwakwa

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Objective: As novel and better tolerated therapies become available, effective HCV testing and care models become increasingly necessary to not only identify individuals with active infection but also link them to HCV providers for medical evaluation and treatment. Our aim is to describe an effective HCV testing and linkage to care model piloted in a network of five community health centers located in Philadelphia, PA. Methods: In October 2012, National Nursing Centers Consortium piloted a routine opt-out HCV testing model in a network of community health centers, one of which treats HCV, HIV, and co-infected patients. Key aspects of the model were medical assistant initiated testing, the use of laboratory-based reflex test technology, and electronic medical record modifications to prompt, track, report and facilitate payment of test costs. Universal testing on all adult patients was implemented at health centers serving patients at high-risk for HCV. The other sites integrated high-risk based testing, where patients meeting one or more of the CDC testing recommendation risk factors or had a history of homelessness were eligible for HCV testing. Mid-course adjustments included the integration of dual HIV testing, development of a linkage to care coordinator position to facilitate the transition of HIV and/or HCV-positive patients from primary to specialist care, and the transition to universal HCV testing across all testing sites. Results: From October 2012 to June 2015, the health centers performed 7,730 HCV tests and identified 886 (11.5%) patients with a positive HCV-antibody test. Of those with positive HCV-antibody tests, 838 (94.6%) had an HCV-RNA confirmatory test and 590 (70.4%) progressed to current HCV infection (overall prevalence=7.6%); 524 (88.8%) received their RNA-positive test result; 429 (72.7%) were referred to an HCV care specialist and 271 (45.9%) were seen by the HCV care specialist. The best linkage to care results were seen at the test and treat the site, where of the 333 patients were current HCV infection, 175 (52.6%) were seen by an HCV care specialist. Of the patients with active HCV infection, 349 (59.2%) were unaware of their HCV-positive status at the time of diagnosis. Since the integration of dual HCV/HIV testing in September 2013, 9,506 HIV tests were performed, 85 (0.9%) patients had positive HIV tests, 81 (95.3%) received their confirmed HIV test result and 77 (90.6%) were linked to HIV care. Dual HCV/HIV testing increased the number of HCV tests performed by 362 between the 9 months preceding dual testing and first 9 months after dual testing integration, representing a 23.7% increment. Conclusion: Our HCV testing model shows that integrated routine testing and linkage to care is feasible and improved detection and linkage to care in a primary care setting. We found that prevalence of current HCV infection was higher than that seen in locally in Philadelphia and nationwide. Intensive linkage services can increase the number of patients who successfully navigate the HCV treatment cascade. The linkage to care coordinator position is an important position that acts as a trusted intermediary for patients being linked to care.

Keywords: HCV, routine testing, linkage to care, community health centers

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Authors: Marisa Chrysochoou, James Mahoney, Kay Wille

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Pyrrhotite is an iron-sulfide mineral which releases sulfuric acid when exposed to water and oxygen. The presence of this mineral in concrete foundations across Connecticut and Massachusetts in the US is causing in some cases premature failure. This has resulted in a devastating crisis for all parties affected by this type of failure which can take up to 15-25 years before internal damage becomes visible on the surface. This study shares laboratory results aimed to investigate the fundamental mechanisms of pyrrhotite reaction and to further the understanding of its deterioration kinetics within concrete. This includes the following analyses: total sulfur, wavelength dispersive X-ray fluorescence, expansion, reaction rate combined with ion-chromatography, as well as damage evolution using electro-chemical acceleration. This information is coupled to a statistical analysis of over 150 analyzed concrete foundations. Those samples were obtained and process using a developed and validated sampling method that is minimally invasive to the foundation in use, provides representative samples of the concrete matrix across the entire foundation, and is time and cost-efficient. The processed samples were then analyzed using a developed modular testing method based on total sulfur and wavelength dispersive X-ray fluorescence analysis to quantify the amount of pyrrhotite. As part of the statistical analysis the results were grouped into the following three categories: no damage observed and no pyrrhotite detected, no damage observed and pyrrhotite detected and damaged observed and pyrrhotite detected. As expected, a strong correlation between amount of pyrrhotite, age of the concrete and damage is observed. Information from the laboratory investigation and from the statistical analysis of field samples will aid in forming a scientific basis to support the decision process towards sustainable financial and administrative solutions by state and local stakeholders.

Keywords: concrete, pyrrhotite, risk of failure, statistical analysis

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Authors: Jawaher F. Alsharef, Abdullah A. Ghaddaf, Mohammed S. Alomari, Abdullah A. Al Qurashi, Ahmed S. Abdulhamid, Mohammed S. Alshehri, Majed Alosaimi

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Botulinum toxin type A (BTX-A) is the most popular therapeutic agent for muscle relaxation and pain control. Lately, BTX-A injection received great interest as a part of multimodal pain management for lower limb lengthening and deformity correction. This systematic review aimed to determine the role of BTX-A injection in pain management for during lower limb lengthening and/or deformity correction. We searched Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared the BTX-A injection to placebo for individuals undergoing lower limb lengthening and/or deformity correction. We sought to evaluate the following outcomes: pain on visual analogue scale (VAS), range of motion parameters, average opioid consumption, and adverse events. The standardized mean difference (SMD) was used to represent continuous outcomes while risk ratio (RR) was used to represent dichotomous outcomes. A total of 4 RCTs that enrolled 257 participants (337 limbs) deemed eligible. Adjuvant BTX-A injection showed a significant reduction in post-operative pain compared to placebo (SMD=–0.28, 95% CI –0.53 to –0.04). No difference was found between BTX-A injection and placebo in terms of range of motion parameters, average opioid consumption, or adverse events after surgical limb lengthening and/or deformity correction (RR= 0.77, 95% CI –0.58 to 1.03). Conclusions: Adjuvant BTX-A injection conferred a discernible reduction in post-operative pain during surgical limb lengthening and/or deformity without increasing the risk of adverse events.

Keywords: botulinum toxin type A, limb lengthening, distraction osteogenesis, deformity correction, pain management

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Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia

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Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.

Keywords: machining, infrared thermography, FEM, temperature measurement

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Authors: Ildiko Fekete-Kertesz, Jade Chaker, Sylvain Berthelot, Viktoria Feigl, Monika Molnar, Lidia Favier

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There has been growing concern about emerging micropollutants in recent years, because of the possible environmental and health risk posed by these substances, which are released into the environment as a consequence of anthropogenic activities. Among them pharmaceuticals are currently not considered under water quality regulations; however, their potential effect on the environment have become more frequent in recent years. Due to the fact that these compounds can be detected in natural water matrices, it can be concluded, that the currently applied water treatment processes are not efficient enough for their effective elimination. To date, advanced oxidation processes (AOPs) are considered as highly competitive water treatment technologies for the removal of those organic micropollutants not treatable by conventional techniques due to their high chemical stability and/or low biodegradability. AOPs such as (photo)chemical oxidation and heterogeneous photocatalysis have proven their potential in degrading harmful organic compounds from aqueous matrices. However, some of these technologies generate reaction by-products, which can even be more toxic to aquatic organisms than the parent compounds. Thus, target compound removal does not necessarily result in the removal of toxicity. Therefore, to evaluate process efficiency the determination of the toxicity and ecotoxicity of the reaction intermediates is crucial to estimate the environmental risk of such techniques. In this context, the present study investigates the effectiveness of TiO2 assisted photodegradation for the removal of emerging water contaminants. Two drugs named losartan (used in high blood pressure medication) and levetiracetam (used to treat epilepsy) were considered in this work. The photocatalytic reactions were carried out with a commercial catalyst usually employed in photocatalysis. Moreover, the toxicity of the by-products generated during the process was assessed with various ecotoxicological methods applying aquatic test organisms from different trophic levels. A series of experiments were performed to evaluate the toxicity of untreated and treated solutions applying the Aliivibrio fischeri bioluminescence inhibition test, the Tetrahymena pyriformis proliferation inhibition test, the Daphnia magna lethality and immobilization tests and the Lemna minor growth inhibition test. The applied ecotoxicological methodology indicated sensitively the toxic effects of the treated and untreated water samples, hence the applied test battery is suitable for the ecotoxicological characterization of TiO2 based photocatalytic water treatment technologies and the indication of the formation of toxic by-products from the parent chemical compounds. Obtained results clearly showed that the TiO2 assisted photodegradation was more efficient in the elimination of losartan than levetiracetam. It was also observed that the treated levetiracetam solutions had more severe effect on the applied test organisms. A possible explanation would be the production of levetiracetam by-products, which are more toxic than the parent compound. The increased toxicity and the risk of formation of toxic metabolites represent one possible limitation to the implementation of photocatalytic treatment using TiO2 for the removal of losartan and levetiracetam. Our results proved that, the battery of ecotoxicity tests used in this work can be a promising investigation tool for the environmental risk assessment of photocatalytic processes.

Keywords: aquatic micropollutants, ecotoxicology, nano titanium dioxide, photocatalysis, water treatment

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Authors: Bintou Jobe

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Musculo-skeletal disorders (MSDs) are injuries or disorders of the spine disc, muscle strains, and low back injuries. It remains a major cause of occupational illness. Findings: Due to poor grips during handling, it is possible for neck, shoulder, arm, knees, ankle, fingers, waist, lower back injuries, and other muscle joints to be affected. Pregnant women are more prone to physical and hormonal changes, which lead to the relaxation of supporting ligaments. MSD continues to pose a global concern due to its impact on workers worldwide. The prevalence of the disorder is high, according to research into the workforce in Europe and developing countries. The causes are characterized by long working hours, insufficient rest breaks, poor posture, repetitive motion, poor manual handling techniques, psychological stress, and poor nutrition. To prevent MSD, the design mainly involves avoiding and assessing the risk. However, clinical solutions, policy governance, and minimizing manual labour are also an alternative. In addition, eating a balanced diet and teamwork force are key to elements in minimising the risk. This review aims to raise awareness and promote cost effectiveness prevention and understanding of MSD through research and identify proposed solutions to recognise the underlying causes of MSDs in the construction sectors. The methodology involves a literature review approach, engaging with the policy landscape of MSD, synthesising publications on MSD and a wider range of academic publications. In conclusion, training on effective manual handling techniques should be considered, and Personal Protective Equipment should be a last resort. The implementation of training guidelines has yielded significant benefits.

Keywords: musculoskeletal disorder work related, MSD, manual handling, work hazards

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Authors: Syed Noaman Shah

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The current paper evaluates the effect of external public debt risk on the borrowing cost of private non-financial firms in euro zone. Further, the study also treats the impact of austerity measures on syndicated-loan spreads of private firm followed by euro area member states to revive the economic growth in the region. To test these hypotheses, we follow multivariate ordinary least square estimation method to assess the effect of external public debt on the borrowing cost of private firms. By using foreign syndicated-loan issuance data of non-financial private firms from 2005 to 2011, we attempt to gauge how the private financing cost varies with high levels of sovereign external debt prevalent in the euro zone. Our results suggest significant effect of external public debt on the borrowing cost of private firm. In particular, an increase in external public debt by one standard deviation from its sample mean raises syndicated-loan spread by 89 bps. Furthermore, weak creditor rights protection prevalent in member states deepens this effect. However, we do not find any significant effect of domestic public debt on the private sector borrowing cost. In addition, the results show significant effect of austerity measures on private financing cost, both in normal and in crisis period in the euro zone. In particular, one standard deviation change in fiscal consolidation conditional mean reduces the syndicated-loan spread by 22 bps. In turn, it indicates strong presence of credibility channel due to austerity measures in euro area region.

Keywords: corporate debt, fiscal consolidation, sovereign debt, syndicated-loan spread

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Authors: Djarot B. Darmadi

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The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo-Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.

Keywords: residual stress, ferritic steels, SSPT, coupled-TMM

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model

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Authors: A. G. Barua, Uttam Rajkhowa, Pranjal Moni Nath, Nur Abdul Kadir

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Mycobacterium tuberculosis (MTB) is one of the most closely-related intracellular bacterial pathogens, grouped as the M. tuberculosis complex (MTC). MTB, the primary agent of human tuberculosis (TB), can develop clinical TB in animals as 75 percent of canine mycobacterial infection is caused by close contact with an infected human being. In the present study, molecular detection of TB in dogs in three North-eastern states of India, Assam Mizoram, and Nagaland was carried out. So far, there has been a lack of systematic study in these regions, hampered by slow diagnostic methods and poor infrastructure. In an attempt to rectify this situation, molecular epidemiology was carried out for nine months to detect canine TB in a sample of 340 dogs. Isolation of DNA was done with swabs (throat/nasal), nodules of lungs and fluids from 100 suspected dogs and the molecular study were carried out with the help of conventional and real-time PCR. Post-mortem study was also carried out. Our results showed that the prevalence of clinical TB in dogs from a high-risk setting was 1 percent. However, the prevalence of immunological sensitization to M. tuberculosis antigen in dogs living in contact with sputum smeared positive TB cases was almost 50 percent. The latter setting had the maximum impact in terms of TB transmission. During the study period, a survey with a standard questionnaire was carried out in the TB hospitals to study reverse zoonosis. It was observed that an infected human being was one of the major risk factors for dogs to contract the infection. This observation was drawn by examining the probable airborne transmission from humans to their pets or strays. The present study helped to discover the nuances of TB transmission more clearly and systematically as compared to other sporadic tests to detect MTB in canine.

Keywords: Assam and Nagaland, canine TB, India, molecular detection, tuberculosis

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Authors: Surya Prasad Sharma, Suyash Katdare, Syed Ainul Hussain

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Human-induced factors contributed to the population decline of crocodylians in India which became evident by the mid-20th century when authorities forewarned the extinction risk for the crocodile and proposed regulation in the crocodile trade. The proposed action led to the enactment of national and international wildlife regulations to prohibit the trade-in of crocodile skins and parts. Subsequently, conservation translocation programs were initiated to restore the species in the wild through a 'head-start' approach. In India, the crocodile conservation program, which began in the early 1970s, has been one of India's longest-running conservation initiatives. The gharial (Gavialis gangeticus) population has benefitted, and the gharial number increased rapidly owing to these efforts. The immediate risk of extinction was averted as the gharial has recovered due to decades-long cumulative conservation efforts, the consideration of the genetic for monitoring the recovery of the recovered populations is still lacking. Hence, we assessed the genetic diversity of the Girwa gharial population in India using six polymorphic nuclear microsatellites loci and mitochondrial control region. The number of alleles per loci ranged between 2 to 5, and the allelic richness (Ar) was 2.67 ± 0.49, and the observed (Ho) and expected (He) heterozygosities were 0.42 ± 0.08 and 0.42 ± 0.09, respectively. The M-ratio yielded a value of (0.41 ± 0.16) lower than critical M, suggesting a genetic bottleneck in the Girwa population. We observed more mitochondrial control region haplotypes in the Girwa population than previously reported in the largest gharial population in the Chambal River. Overall, our study indicates that genetic diversity remains low despite the recovery in the Girwa population. Hence, we recommend a range-wide genetic assessment of gharial populations using high-throughput techniques to identify the source population and plan future translocation programs.

Keywords: conservation translocation, recovery, crocodile, bottleneck

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Franck Acho

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This is a chronic metabolic disorder which is a fast-growing global problem with a huge social, health, and economic consequences. It is estimated that in 2010 there were globally 285 million people (approximately 6.4% of the adult population) suffering from this disease. This number is estimated to increase to 430 million in the absence of better control or cure. An ageing population and obesity are two main reasons for the increase. Diabetes mellitus is a chronic heterogeneous metabolic disorder with a complex pathogenesis. It is characterized by elevated blood glucose levels or hyperglycemia, which results from abnormalities in either insulin secretion or insulin action or both. Hyperglycemia manifests in various forms with a varied presentation and results in carbohydrate, fat, and protein metabolic dysfunctions. Long-term hyperglycemia often leads to various microvascular and macrovascular diabetic complications, which are mainly responsible for diabetes-associated morbidity and mortality. Hyperglycemia serves as the primary biomarker for the diagnosis of diabetes as well. Furthermore, it has been shown that almost 50% of the putative diabetics are not diagnosed until 10 years after onset of the disease, hence the real prevalence of global diabetes must be astronomically high. This study was conducted in a locality to access the level of knowledge, awareness and risk factors associated with people leaving with diabetes mellitus. A month before the screening was to be conducted, a health screening in some selected churches and on the local community radio as well as on relevant WhatsApp groups were advertised. A general health talk was delivered by the head of the screening unit to all attendees who were all educated on the procedure to be carried out with benefits and any possible discomforts after which the attendee’s consent was obtained. Evaluation of the participants for any leads to the diabetes selected for the screening was done by taking adequate history and physical examinations such as excessive thirst, increased urination, tiredness, hunger, unexplained weight loss, feeling irritable or having other mood changes, having blurry vision, having slow-healing sores, getting a lot of infections, such as gum, skin and vaginal infections. Out of the 94 participants the finding show that 78 were females and 16 were males, 70.21% of participants with diabetes were between the ages of 60-69yrs.The study found that only 10.63% of respondents declared a good level of knowledge of diabetes. Out of 3 symptoms of diabetes analyzed in this study, high blood sugar (58.5%) and chronic fatigue (36.17%) were the most recognized. Out of 4 diabetes risk factors analyzed in this study, obesity (21.27%) and unhealthy diet (60.63%) were the most recognized diabetes risk factors, while only 10.6% of respondents indicated tobacco use. The diabetic foot was the most recognized diabetes complication (50.57%), but some the participants indicated vision problems (30.8%),or cardiovascular diseases (20.21%) as diabetes complications.

Keywords: diabetes mellitus, non comunicable disease, general health talk, hyperglycemia

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Authors: Luisa Windhagen, Atsumi Hirose, Alex Bottle

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Global urbanization has resulted in the expansion of slums, leaving over 10 million Tanzanians in urban poverty and at risk of poor health. Whilst rural residence has historically been associated with an increased risk of adverse pregnancy outcomes, recent studies found higher perinatal mortality rates in urban Tanzania. This study aims to understand to what extent slum neighborhoods may account for the spatial disparities seen in Tanzania. We generated a slum indicator based on UN-HABITAT criteria to identify slum clusters within the 2015-2016 Tanzania Demographic and Health Survey. Descriptive statistics, disaggregated by urban slum, urban non-slum, and rural areas, were produced. Simple and multivariable logistic regression examined the association between cluster residence type and neonatal mortality and stillbirth. For neonatal mortality, we additionally built a multilevel logistic regression model, adjusting for confounding and clustering. The neonatal mortality ratio was highest in slums (38.3 deaths per 1000 live births); the stillbirth rate was three times higher in slums (32.4 deaths per 1000 births) than in urban non-slums. Neonatal death was more likely to occur in slums than in urban non-slums (aOR=2.15, 95% CI=1.02-4.56) and rural areas (aOR=1.78, 95% CI=1.15-2.77). Odds of stillbirth were over five times higher among rural than urban non-slum residents (aOR=5.25, 95% CI=1.31-20.96). The results suggest that slums contribute to the urban disadvantage in Tanzanian neonatal health. Higher neonatal mortality in slums may be attributable to lack of education, lower socioeconomic status, poor healthcare access, and environmental factors, including indoor and outdoor air pollution and unsanitary conditions from inadequate housing. However, further research is required to ascertain specific causalities as well as significant associations between residence type and other pregnancy outcomes. The high neonatal mortality, stillbirth, and slum formation rates in Tanzania signify that considerable change is necessary to achieve international goals for health and human settlements. Disparities in access to adequate housing, safe water and sanitation, high standard antenatal, intrapartum, and neonatal care, and maternal education need to urgently be addressed. This study highlights the spatial neonatal mortality shift from rural settings to urban informal settlements in Tanzania. Importantly, other low- and middle-income countries experiencing overwhelming urbanization and slum expansion may also be at risk of a reversing trend in residential neonatal health differences.

Keywords: urban health, slum residence, neonatal mortality, stillbirth, global urbanisation

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Authors: J. DeBoard, R. Dietrich, J. Hughes, K. Yurko, G. Harms

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Alzheimer’s disease (AD) is a predominant type of dementia and is likely a major cause of neural network impairment. The pathogenesis of this neurodegenerative disorder has yet to be fully elucidated. There are currently no known cures for the disease, and the best hope is to be able to detect it early enough to impede its progress. Beyond age and genetics, another prevalent risk factor for AD might be traumatic brain injury (TBI), which has similar neurodegenerative hallmarks. Our research focuses on obtaining information and methods to be able to predict when neurodegenerative effects might occur at a clinical level by observation of events at a cellular and molecular level in model mice. First, we wish to introduce our evidence that brain damage can be observed via brain imaging prior to the noticeable loss of neuromuscular control in model mice of AD. We then show our evidence that some blood biomarkers might be able to be early predictors of AD in the same model mice. Thus, we were interested to see if we might be able to predict which mice might show long-term neurodegenerative effects due to differing degrees of TBI and what level of TBI causes further damage and earlier death to the AD model mice. Upon application of TBIs via an apparatus to effectively induce extremely mild to mild TBIs, wild-type (WT) mice and AD mouse models were tested for cognition, neuromuscular control, olfactory ability, blood biomarkers, and brain imaging. Experiments are currently still in process, and more results are therefore forthcoming. Preliminary data suggest that neuromotor control diminishes as well as olfactory function for both AD and WT mice after the administration of five consecutive mild TBIs. Also, seizure activity increases significantly for both AD and WT after the administration of the five TBI treatment. If future data supports these findings, important implications about the effect of TBI on those at risk for AD might be possible.

Keywords: Alzheimer's disease, blood biomarker, neurodegeneration, neuromuscular control, olfaction, traumatic brain injury

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: G. K. Pandey, D. Ramadasu, I. Banerjee, V. Vinod, G. Padmakumar, V. Prakash, K. K. Rajan

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Detailed thermal hydraulic investigations are very essential for safe and reliable functioning of liquid metal cooled fast breeder reactors. These investigations are further more important for components with complex profile, since there is no direct correlation available in literature to evaluate the hydraulic characteristics of such components directly. In those cases available correlations for similar profile or geometries may lead to significant uncertainty in the outcome. Hence experimental approach can be adopted to evaluate these hydraulic characteristics more precisely for better prediction in reactor core components. Prototype Fast Breeder Reactor (PFBR), a sodium cooled pool type reactor is under advanced stage of construction at Kalpakkam, India. Several components of this reactor core require hydraulic investigation before its usage in the reactor. These hydraulic investigations on full scale models, carried out by experimental approaches using water as simulant fluid are discussed in the paper.

Keywords: fast breeder reactor, cavitation, pressure drop, reactor components

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Authors: Martin Hofmann, Diego Stutzer, Thomas Niederhauser, Juergen Burger

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Dental biofilm is the main etiologic factor for caries, periodontal and peri-implant infections. In addition to the risk of tooth loss, periodontitis is also associated with an increased risk of systemic diseases such as atherosclerotic cardiovascular disease and diabetes. For this reason, dental hygienists use ultrasonic scalers for prophylactic and periodontal care of the teeth. However, the current instruments are limited to their dimensions and operating frequencies. The innovative design of a planar ultrasonic transducer introduces a new type of dental scalers. The flat titanium-based design allows the mass to be significantly reduced compared to a conventional screw-mounted Langevin transducer, resulting in a more efficient and controllable scaler. For the development of the novel device, multi-physics finite element analysis was used to simulate and optimise various design concepts. This process was supported by prototyping and electromechanical characterisation. The feasibility and potential of a planar ultrasonic transducer have already been confirmed by our current prototypes, which achieve higher performance compared to commercial devices. Operating at the desired resonance frequency of 28 kHz with a driving voltage of 40 Vrms results in an in-plane tip oscillation with a displacement amplitude of up to 75 μm by having less than 8 % out-of-plane movement and an energy transformation factor of 1.07 μm/mA. In a further step, we will adapt the design to two additional resonance frequencies (20 and 40 kHz) to obtain information about the most suitable mode of operation. In addition to the already integrated characterization methods, we will evaluate the clinical efficiency of the different devices in an in vitro setup with an artificial biofilm pocket model.

Keywords: ultrasonic instrumentation, ultrasonic scaling, piezoelectric transducer, finite element simulation, dental biofilm, dental calculus

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