Search results for: closed loop identification

Authors: A. Berraf-Tebbal, Z. Bouznad, , A.J.L. Phillips

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Phaeomoniella is a fungus genus in the mitosporic ascomycota which includes Phaeomoniella chlamydospora specie associated with two declining diseases on grapevine (Vitis vinifera) namely Petri disease and esca. Recent studies have shown that several Phaeomoniella species also cause disease on many other woody crops, such as forest trees and woody ornamentals. Two new species, Phaeomoniella zymoides and Phaeomoniella pinifoliorum H.B. Lee, J.Y. Park, R.C. Summerbell et H.S. Jung, were isolated from the needle surface of Pinus densiflora Sieb. et Zucc. in Korea. The identification of species in Phaeomoniella genus can be a difficult task if based solely on morphological and cultural characters. In this respect, the application of molecular methods, particularly PCR-based techniques, may provide an important contribution. MSP-PCR (microsatellite primed-PCR) fingerprinting has proven useful in the molecular typing of fungal strains. The high discriminatory potential of this method is particularly useful when dealing with closely related or cryptic species. In the present study, the application of PCR fingerprinting was performed using the micro satellite primer M13 for the purpose of species identification and strain typing of 84 Phaeomoniella -like isolates collected from grapevines with typical symptoms of dieback. The bands produced by MSP-PCR profiles divided the strains into 3 clusters and 5 singletons with a reproducibility level of 80%. Representative isolates from each group and, when possible, isolates from Eutypa dieback and esca symptoms were selected for sequencing of the ITS region. The ITS sequences for the 16 isolates selected from the MSP-PCR profiles were combined and aligned with sequences of 18 isolates retrieved from GenBank, representing a selection of all known Phaeomoniella species. DNA sequences were compared with those available in GenBank using Neighbor-joining (NJ) and Maximum-parsimony (MP) analyses. The phylogenetic trees of the ITS region revealed that the Phaeomoniella isolates clustered with Phaeomoniella chlamydospora reference sequences with a bootstrap support of 100 %. The complexity of the pathosystems vine-trunk diseases shows clearly the need to identify unambiguously the fungal component in order to allow a better understanding of the etiology of these diseases and justify the establishment of control strategies against these fungal agents.

Keywords: Genotyping, MSP-PCR, ITS, phylogeny, trunk diseases

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Authors: Djebbar Atmani, Aghiles Karim Aissat, Nadjet Debbache-Benaida, Nassima Chaher-Bazizi, Dina Atmani-Kilani, Meriem Rahmani-Berboucha, Naima Saidene, Malika Benloukil, Lila Azib

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Medicinal plants are believed to be an important source for the discovery of potential antioxidant, anti-inflammatory and anti-diabetic substances. The present study was designed to investigate the neuroprotective, anti-inflammatory, anti-diabetic and anti-hyperuricemic potential of Pistacia lentiscus, as well as the identification of active compounds. The antioxidant potential of plant extracts against known radicals was measured using various standard in vitro methods. Anti-inflammatory activity was determined using the paw edema model in mice and by measuring the secretion of the pro-inflammatory cytokine, whereas the anti-diabetic effect was assessed in vivo on streptozotocin-induced diabetic rats and in vitro by inhibition of alpha-amylase. The anti-hyperuricemic activity was evaluated using the xanthine oxidase assay, whereas neuroprotective activity was investigated using an Aluminum-induced toxicity test. Pistacia lentiscus extracts and fractions exhibited high scavenging capacity against DPPH, NO. and ABTS+ radicals in a dose-dependent manner and restored blood glucose levels, in vivo, to normal values, in agreement with the in vitro anti-diabetic effect. Oral administration of plant extracts significantly decreased carrageenan-induced mice paw oedema, similar to the standard drug, diclofenac, was effective in reducing IL-1β levels in cell culture and induced a significant increase in urinary volume in mice, associated to a promising anti-hyperuricemic activity. Plant extracts showed good neuroprotection and restoration of cognitive functions in mice. HPLC-MS and NMR analyses allowed the identification of known and new phenolic compounds that could be responsible for the observed activities. Therefore, Pistacia lentiscus could be beneficial in the treatment of inflammatory conditions and diabetes complications and the enhancement of cognitive functions.

Keywords: Pistacia lentiscus, anti-inflammatory, antidiabetic, flavanols, neuroprotective

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Authors: Sahar Nasr, Lin Li, Edwin Wang

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Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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Authors: Anukwu John Uchenn, Nwamba, Helen Ogochukwu, Achikanu Cosmas, Chiaha Emiliana

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The continuous decline in biodiversity is worrisome. This decline is predominant in fish population. Although taxonomy has been an age-long field of science, there are still undiscovered members of species and new species are waiting to be uncovered. The failure of traditional taxonomic method to address this issue has resulted to the adoption of a molecular approach-DNA barcoding. It was proposed that DNA barcoding using mitochondrion cytochrome oxidase subunit I (COI) gene has the capability to serve as a barcode for fishes. The aim of this study was to use DNA barcoding in the identification of fish species in Imo River, Rivers State. A total of eight (8) fish samples were collected and used for this study. Quick DNA Miniprep Plus kit (D4068, Zymo Research) was used for the DNA extraction which was followed by PCR amplification and sequencing. BLAST result shows correlation between the sequence queried and the biological sequences with the NCBI database. The names of the samples, percentage ID, predicted organisms and GenBank Accession numbers were clearly identified. A total of 16 sequences (all > 600bp) belonging to 7 species, 7 genera, 7 families and 4 orders were validated and submitted to the NCBI database. Each nucleotide peak was represented by a single colour with various percentage occurrences. Four (50%) out of the 8 original samples analyzed corresponded with the predicted organisms from BLAST result. Pairwise sequence alignment showed different consensus positions and a total of 11 mutations found in Chrysichthys nigrodigitatus (n=4), Oreochromis niloticus (n=2) and Clarias gariepinus (n=5). The whole mutations were substitution (transition and transversion) with no deletion and insertion. However, the transition mutation (n=6) was more in number compared to the transversion (n=5) mutation. There were a total of 834 positions in the final dataset. This work will facilitate more research in other keys areas such as identification of mislabeled fish products, illegal trading of endangered species and effective tracking of fish biodiversity.

Keywords: DNA barcoding, Imo river, phylogenetic tree, pairwise DNA alignment

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Authors: Jinah Kwon

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Why are there North Korean women who prefer their life in China, living as an undocumented migrant, to legal residence in South Korea? What is the line between choice and coercion in trafficking and how does it relate to family, especially in Asian culture? Is family function as a haven in the unsecured world or a fetter against the better world? Are the current international mechanisms on trafficked victims fully reflecting the voices of the victims? This study is about the paradoxical conditions of North Korean women situated in China as the trafficked victim and as members of their Chinese family. In order to answer the questions above, this study explored the case of trafficked North Korean women in China. This mixed-methods study employed in-depth interviews of 18 trafficked women living in China and a survey of 98 North Korean origin women residing in South Korea. From the survey, 40 out of 98 women from the survey indicated an unexpected function of trafficking, which was used as a channel of supporting the subjectivity of women in the North Korean context. Such results supported the actual observation and narratives of North Korean women who experienced trafficking from the author’s two visits to the Northeastern area of China in 2012 and 2018, respectively. Based on the findings, the last part of the study makes policy implications on international trafficking mechanisms—theories by Gayatri Spivak and Herbert A. Simon was employed to approach the relatively less dealt aspect of trafficking.

Keywords: China, North Korean women, trafficking, victimhood

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Authors: H. N. S. Silva, S. N. Silva

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Introduction: 88.3% of physicians decided to choose a ‘no-code’ or a DNR order if hospitalized and would choose to die less aggressively at home. However, their wishes were mostly over ridden. Objective: To assess the attitudes of nurses towards the end-of-the-life care they would like to receive for themselves and their attitudes towards terminal illnesses. Methods: A mixed method approach was used. A closed and open-ended questionnaire was administered to 73 participants and 5 registered nurses, who have more than 10 years of experience, working in hospitals both in Sri Lanka and abroad, were interviewed. Results: 94.1% of the participants stated that they would like to die at home, spending their last hours at home surrounded by their loved ones and engaging in religious activities but 57.7% of unmarried nurse said they would agree on euthanasia if they had a terminal disease, and also 66.2% of them stated they would agree in DNR order if they happen to be admitted to the ICU, but 82.5% wanted to diagnose if they had a terminal illness or cancer but did not agree on euthanasia. Qualitative analysis confirmed the findings and revealed that despite having adequate confidence about the hospital care, nurses would choose to die at home, surrounded by their loved once and engaging in religious activities. Euthanasia was believed to be inappropriate as it is religiously incorrect and as death is a natural process. Conclusion: The perception of death among nurses depends on their religious belief.

Keywords: death, do not resuscitate, euthanasia, nurses

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Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

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Authors: Jamie Lee Harder

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In the context of rapidly changing social and economic circumstances in the developing world, this paper analyses access to public healthcare for poor people with disabilities in Cambodia. Like other countries of South East Asia, Cambodia is developing at rapid pace. The historical past of Cambodia, however, has set former social policy structures to zero. This past forces Cambodia and its citizens to implement new public health policies to align with the needs of social care, healthcare, and urban planning. In this context, the role of people with disabilities (PwDs) is crucial as new developments should and can take into consideration their specific needs from the beginning onwards. This paper is based on qualitative research with expert interviews and focus group discussions in Cambodia. During the field work it became clear that the identification tool for the poorest households (HHs) does not count disability as a financial risk to fall into poverty neither when becoming sick nor because of higher health expenditures and/or lower income because of the disability. The social risk group of poor PwDs faces several barriers in accessing public healthcare. The urbanization, the socio-economic health status, and opportunities for education; all influence social status and have an impact on the health situation of these individuals. Cambodia has various difficulties with providing access to people with disabilities, mostly due to barriers regarding finances, geography, quality of care, poor knowledge about their rights and negative social and cultural beliefs. Shortened budgets and the lack of prioritizations lead to the need for reorientation of local communities, international and national non-governmental organizations and social policy. The poorest HHs are identified with a questionnaire, the IDPoor program, for which the Ministry of Planning is responsible. The identified HHs receive an ‘Equity Card’ which provides access free of charge to public healthcare centers and hospitals among other benefits. The dataset usually does not include information about the disability status. Four focus group discussions (FGD) with 28 participants showed various barriers in accessing public healthcare. These barriers go far beyond a missing ramp to access the healthcare center. The contents of the FGDs were ratified and repeated during the expert interviews with the local Ministries, NGOs, international organizations and private persons working in the field. The participants of the FGDs faced and continue to face high discrimination, low capacity to work and earn an own income, dependency on others and less social competence in their lives. When discussing their health situation, we identified, a huge difference between those who are identified and hold an Equity Card and those who do not. Participants reported high costs without IDPoor identification, positive experiences when going to the health center in terms of attitude and treatment, low satisfaction with specific capacities for treatments, negative rumors, and discrimination with the consequence of fear to seek treatment in many cases. The problem of accessing public healthcare by risk groups can be adapted to situations in other countries.

Keywords: access, disability, health, inequality, Cambodia

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Authors: Shashank Tiwari

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The most common method of drug delivery is the oral solid dosage form, of which tablets and capsules are predominant. The tablet is more widely accepted and used compared to capsules for a number of reasons, such as cost/price, tamper resistance, ease of handling and packaging, ease of identification, and manufacturing efficiency. Over the past several years, the issue of tamper resistance has resulted in the conversion of most over-the-counter (OTC) drugs from capsules to predominantly all tablets.

Keywords: capsule, drug delivery, dosages, solid, tablet

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Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

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Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

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Authors: Yasir E. Mohieldeen

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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.

Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination

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Authors: Salisu Umar

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Fruits are a seasonal crop and get spoiled quickly. They are dried to be preserved for a long period. The natural drying process requires more time. The investment on space requirement and infrastructure is large, and cannot be afforded by a middle class farmer. Therefore there is a need for a comparatively small unit with reduced drying times, which can be afforded by a middle class farmer. A controlled environment suitable for fruit drying is developed within a closed chamber and is a three step process. Firstly, the infrared light is used internally to preheated the fruit to speedily remove the water content inside the fruit for fast drying. Secondly, hot air of a specified temperature is blown inside the chamber to maintain the humidity below a specified level and exhaust the humid air of the chamber. Thirdly the microcontroller idles disconnecting the power to the chamber after the weight of the fruits is reduced to a known value of its original weight. This activates a buzzer for duration of ten seconds to indicate the end of the drying process. The results obtained indicate that the system is significantly reducing the drying time without affecting the quality of the fruits compared with the existing dryers.

Keywords: fruit, fuzzy controller, microcontroller, temperature, weight and humidity

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Zeenath Solih

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The aim of the study is to analyze the factors that influence the decision to pursue a hospitality and tourism program for students of Maldives when pursuing higher education options. This research would further explore the implications and relationship between the universities and students. Quantitative research method will be used to demonstrate the hypothesis and achieve the objectives of this research, a questionnaire consisting of 30 closed questions will be used which will be analyzed based on SPSS18 software to handle and extract the data.10 public school and 3 private schools with secondary education and 3 universities with higher education facilities and a total of 500 students participated in the survey. The findings include selection criteria for decision making for higher studies being the university’s reputation, excellence and quality of educational program, the preference of pursuing further studies from a public over private universities and the academic, cultural and socio demographic factors that influence the students choice of program and university. Finally the study will provide valuable insight to how universities need to market their programs to attract the right students.

Keywords: choice criteria, higher education, hospitality and tourism studies, information sources

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Authors: Altayeb Abdalla Ahmed

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Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations.

Keywords: anthropometry, correlation, limb, Sudanese

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Authors: R. Narasimha Rao, Ch. Sri Chaitanya

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Syntactic foams are closed-cell foams with high specific strength and high compression strength. At Low speeds, the wear rate is sensitive to the sliding speeds and other tribological parameters like applied load and the sliding distance. In the present study, the tribological performance of the polymer-based syntactic foams was reported based on the experiments conducted on a pin-on-disc tribometer. The syntactic foams were manufactured with epoxy as the matrix and the cenospheres obtained from the thermal powerplants as the reinforcement. The experiments were conducted at a sliding speed of the 1 m/s. The applied load was varied from 1 kg to 5 kg up to a sliding distance of 3000 m. The wear rate increased with the sliding distance at lower loads. The trend was reversed at higher loads of 5kg. This may be due to the high plastic deformation at the initial stages when higher loads were applied. This was evident with the higher friction constants for the higher loads. The adhesive wear was found to be predominant for lower loads, while the abrasive wear tracks can be seen in micrographs of samples tested under higher loads.

Keywords: sliding speed, syntactic foams, tribological performance, wear rate

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Authors: Mohammed Al-Bloushi, Sanghyun Jeong, Torove Leiknes

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Biofouling in the open recirculating cooling water systems may cause biological corrosion, which can reduce the performance, increase the energy consummation and lower heat exchange efficiencies of the cooling tower. Seawater cooling towers are prone to biofouling due to the presences of organic and inorganic compounds in the seawater. The availability of organic and inorganic nutrients, along with sunlight and continuous aeration of the cooling tower contributes to an environment that is ideal for microbial growth. Various microorganisms (algae, fungi, and bacteria) can grow in a cooling tower system under certain environmental conditions. The most commonly being used method to control the biofouling in the cooling tower is the addition of biocides such as chlorination. In this study, algae containing diatom and green algae were added to the cooling tower basin, and its viability was monitored in the recirculating cooling seawater loop as well as in the cooling tower basin. Continuous addition of biocides was employed in pilot-scale seawater cooling towers, and it was operated continuously for 2 months. Three different types of oxidizing biocides, namely chlorine, chlorine dioxide and ozone, were tested. The results showed that all biocides were effective in keeping the biological growth to the minimum regardless of algal addition. Amongst the biocides, ozone could reduce 99% of total live cells of bacteria and algae, followed by chlorine dioxide at 97%, while the conventional chlorine showed only 89% reduction in the bioactivities.

Keywords: algae, biocide, biofouling, seawater cooling tower

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Ying Han, Weirong Chen, Qi Li

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An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system.

Keywords: DC microgrid, equivalent minimum hydrogen consumption strategy, energy management, time-varying droop coefficient, droop control

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Authors: Rachel deCatanzaro, Madeline Austen, Ken Tuininga, Kathy St. Laurent, Christina Rohe

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In Canada, the federal Species at Risk Act (SARA) provides protection for wildlife species at risk and a national legislative framework for the conservation or recovery of species that are listed as endangered, threatened, or special concern under Schedule 1 of SARA. Key aspects of the federal species at risk program include the development of recovery documents (recovery strategies, action plans, and management plans) outlining threats, objectives, and broad strategies or measures for conservation or recovery of the species; the identification and protection of critical habitat for threatened and endangered species; and working with groups and organizations to implement on-the-ground recovery actions. Environment Canada’s progress on the development of recovery documents and on the identification and protection of critical habitat in Ontario will be presented, along with successes and challenges associated with on-the ground implementation of recovery actions. In Ontario, Environment Canada is currently involved in several recovery and monitoring programs for at-risk bird species such as the Loggerhead Shrike, Piping Plover, Golden-winged Warbler and Cerulean Warbler and has provided funding for a wide variety of recovery actions targeting priority species at risk and geographic areas each year through stewardship programs including the Habitat Stewardship Program, Aboriginal Fund for Species at Risk, and the Interdepartmental Recovery Fund. Key research needs relevant to the recovery of species at risk have been identified, and include: surveys and monitoring of population sizes and threats, population viability analyses, and addressing knowledge gaps identified for individual species (e.g., species biology and habitat needs). The engagement of all levels of government, the local and international conservation communities, and the scientific research community plays an important role in the conservation and recovery of species at risk in Ontario– through surveying and monitoring, filling knowledge gaps, conducting public outreach, and restoring, protecting, or managing habitat – and will be critical to the continued success of the federal species at risk program.

Keywords: conservation biology, habitat protection, species at risk, wildlife recovery

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Authors: Fu Lin

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We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Al Omari Moahmmed Ahmed

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These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions.

Keywords: weibull distribution, bayesian method, markov chain mote carlo, survival and hazard functions

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: M. Ahmed Eldesouky, S. Nasr, A. Beltagy

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Groundwater is generally considered as the best source for aquaculture as it is well protected from contamination. The most common problem limiting the use of groundwater in Egypt is its high iron, manganese and ammonia content. This problem is often overcome by applying the treatment before use. Aeration in many cases is not enough to oxidize iron and manganese in complex forms with organics. Most of the treatment we use potassium permanganate as an oxidizer followed by a pressurized closed green sand filter. The aim of present study is to investigate the optimum characteristics of groundwater to give lowest iron, manganese and ammonia, maximum production and quality of fish in aquaculture in El-Max Research Station. The major design goal of the system was determined the optimum time for harvesting the treated water, pH, and Glauconite weight to use it for aquaculture process in the research site and achieve the Egyptian law (48/1982) and EPA level required for aquaculture. The water characteristics are [Fe = 0.116 mg/L, Mn = 1.36 mg/L,TN = 0.44 mg/L , TP = 0.07 mg/L , Ammonia = 0.386 mg/L] by using the glauconite filter we obtained high efficiency for removal for [(Fe, Mn and Ammonia] ,but in the Lab we obtained result for (Fe, 43-97), ( Mn,92-99 ), and ( Ammonia, 66-88 )]. We summarized the results to show the optimum time, pH, Glauconite weight, and the best model for design in the region.

Keywords: aquaculture, ammonia in groundwater, groundwater, iron and manganese in water, groundwater treatment

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Authors: Recep Kesli, Gulşah Asik, Cengiz Demir, Onur Turkyilmaz

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Objective: Acinetobacter baumannii (A. baumannii) can cause health-care associated infections, such as bacteremia, urinary tract and wound infections, endocarditis, meningitis, and pneumonia, particularly in intensive care unit patients. In this study, we aimed to evaluate A. baumannii production in sputum and bronchoalveolar lavage and susceptibilities for antibiotics in a 24 months period. Methods: Between October 2013 and September 2015, Acinetobacter baumannii isolated from respiratory tract speciments were evaluated retrospectively. The strains were isolated from the different intensive care units patients. A. baumannii strains were identified by both the conventional methods and aoutomated identification system -VITEK 2 (bio-Merieux, Marcy l’etoile, France). Antibiotic resistance testing was performed by Kirby-Bauer disc diffusion method according to CLSI criteria. Results: All the ninety isolates included in the study were from respiratory tract specimens. While of all the isolated 90 Acinetobacter baumannii strains were found to be resistant (100%), against ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam, resistance rates against other tested antibiotics found as follows; meropenem 77, 86%, imipenem 75, 83%, trimethoprim-sulfamethoxazole (TMP-STX) 69, 76,6%, gentamicin 51, 56,6% and amikacin 48, 53,3%. Colistin was found as the most effective antibiotic against Acinetobacter baumannii, and there were not found any resistant (0%) strain against colistin. Conclusion: This study demonstrated that the no resistance was found in Acinetobacter baumannii against to colistin. High rates of resistance to carbapenems (imipenem and meropenem) and other tested antibiotics (ceftiaxone, ceftazidime, ciprofloxacine, piperacilline-tazobactam, TMP-STX gentamicin and amikacin) also have remarkable resistance rates. There was a significant relationship between demographic features of patients such as age, undergoing mechanical ventilation, length of hospital stay with resistance rates. High resistance rates against antibiotics require implementation of the infection control program and rational use of antibiotics. In the present study, while there were not found colistin resistance, panresistance were found against to ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam.

Keywords: acinetobacter baumannii, antibiotic resistance, multi drug resistance, intensive care unit

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Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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