Search results for: isolation forest method

Authors: Suzan Anwar, Utkarsh Goyal

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Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Utpal Das, Sona Das

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InAs/GaSb type-II superlattice (T2SL) Mid-wave infrared (MWIR) focal plane arrays (FPAs) have recently seen rapid development. However, in small pixel size large format FPAs, the occurrence of high mesa sidewall surface leakage current is a major constraint necessitating proper surface passivation. A simple pixel isolation technique in InAs/GaSb T2SL detector arrays without the conventional mesa etching has been proposed to isolate the pixels by forming a more resistive higher band gap material from the SL, in the inter-pixel region. Here, a single step femtosecond (fs) laser anneal of the T2SL structure of the inter-pixel T2SL regions, have been used to increase the band gap between the pixels by QW-intermixing and hence increase isolation between the pixels. The p-i-n photodiode structure used here consists of a 506nm, (10 monolayer {ML}) InAs:Si (1x10¹⁸cm⁻³)/(10ML) GaSb SL as the bottom n-contact layer grown on an n-type GaSb substrate. The undoped absorber layer consists of 1.3µm, (10ML)InAs/(10ML)GaSb SL. The top p-contact layer is a 63nm, (10ML)InAs:Be(1x10¹⁸cm⁻³)/(10ML)GaSb T2SL. In order to improve the carrier transport, a 126nm of graded doped (10ML)InAs/(10ML)GaSb SL layer was added between the absorber and each contact layers. A 775nm 150fs-laser at a fluence of ~6mJ/cm² is used to expose the array where the pixel regions are masked by a Ti(200nm)-Au(300nm) cap. Here, in the inter-pixel regions, the p+ layer have been reactive ion etched (RIE) using CH₄+H₂ chemistry and removed before fs-laser exposure. The fs-laser anneal isolation improvement in 200-400μm pixels due to spatially selective quantum well intermixing for a blue shift of ~70meV in the inter-pixel regions is confirmed by FTIR measurements. Dark currents are measured between two adjacent pixels with the Ti(200nm)-Au(300nm) caps used as contacts. The T2SL quality in the active photodiode regions masked by the Ti-Au cap is hardly affected and retains the original quality of the detector. Although, fs-laser anneal of p+ only etched p-i-n T2SL diodes show a reduction in the reverse dark current, no significant improvement in the full RIE-etched mesa structures is noticeable. Hence for a 128x128 array fabrication of 8μm square pixels and 10µm pitch, SU8 polymer isolation after RIE pixel delineation has been used. X-n+ row contacts and Y-p+ column contacts have been used to measure the optical response of the individual pixels. The photo-response of these 8μm and other 200μm pixels under a 2ns optical pulse excitation from an Optical-Parametric-Oscillator (OPO), shows a peak responsivity of ~0.03A/W and 0.2mA/W, respectively, at λ~3.7μm. Temporal response of this detector array is seen to have a fast response ~10ns followed typical slow decay with ringing, attributed to impedance mismatch of the connecting co-axial cables. In conclusion, response times of a few ns have been measured in 8µm pixels of a 128x128 array. Although fs-laser anneal has been found to be useful in increasing the inter-pixel isolation in InAs/GaSb T2SL arrays by QW inter-mixing, it has not been found to be suitable for passivation of full RIE etched mesa structures with vertical walls on InAs/GaSb T2SL.

Keywords: band-gap blue-shift, fs-laser-anneal, InAs/GaSb T2SL, Inter-pixel isolation, ns-Response, photodiode array

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Authors: Chales Mumbere Musavandalo, Lucie B. Mugherwa, Gloire Kayitoghera Mulondi, Naanson Bweya, Muyisa Musongora, Francis Lelo Nzuzi

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The landscape of the Okapi Wildlife Reserve in the Democratic Republic of Congo harbors a large community of Mbuti indigenous peoples, often described as the guardians of nature. Living in and off the forest has long been a sustainable strategy for preserving natural resources. This strategy, seen as a form of eco-responsible citizenship, draws upon ethnobotanical knowledge passed down through generations. However, these indigenous communities are facing socio-cultural upheaval, which impacts their traditional way of life. This study aims to assess the relationship between the Mbuti indigenous people’s way of life and the preservation of the Okapi Wildlife Reserve. The study was conducted under the assumption that, despite socio-cultural upheavals, the forest and its resources remain central to the Mbuti way of life. The study was conducted in six encampments, three of which were located inside the forest and two in the anthropized zone. The methodological approach initially involved group interviews in six Mbuti encampments. The objective of these interviews was to determine how these people perceive the various services provided by the forest and the resources obtained from this habitat. The technique of using pebbles was adopted to adapt the exercise of weighting services and resources to the understanding of these people. Subsequently, the study carried out ethnobotanical surveys to identify the wood resources frequently used by these communities. This survey was completed in third position by a transect inventory of 1000 m length and 25 m width in order to enhance the understanding of the abundance of these resources around the camps. Two transects were installed in each camp to carry out this inventory. Traditionally, the Mbuti communities sustain their livelihood through hunting, fishing, gathering for self-consumption, and basketry. The Manniophyton fulvum-based net remains the main hunting tool. The primary forest and the swamp are two habitats from which these peoples derive the majority of their resources. However, with the arrival of the Bantu people, who introduced agriculture based on cocoa production, the Mbuti communities started providing services to the Bantu in the form of labor and field guarding. This cultural symbiosis between Mbute and Bantu has also led to non-traditional practices, such as the use of hunting rifles instead of nets and fishing nets instead of creels. The socio-economic and ecological environment in which Mbuti communities live is changing rapidly, including the resources they depend on. By incorporating the time factor into their perception of ecosystem services, only their future (p-value = 0, 0,121), the provision of wood for energy (p-value = 0,1976), and construction (p-value = 0,2548) would be closely associated with the forest in their future. For other services, such as food supply, medicine, and hunting, adaptation to Bantu customs is conceivable. Additionally, the abundance of wood used by the Mbuti people has been high around encampments located in intact forests and low in those in anthropized areas. The traditional way of life of the Mbuti communities is influenced by the cultural symbiosis, reflected in their habits and the availability of resources. The land tenure security of Mbuti areas is crucial to preserve their tradition and forest biodiversity. Conservation efforts in the Okapi Wildlife Reserve must consider this cultural dynamism and promote positive values for the flagship species. The oversight of subsistence hunting is imperative to curtail the transition of these communities to poaching.

Keywords: traditional life, conservation, Indigenous people, cultural symbiosis, forest

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Authors: Vandana T. Gawande, Kailash G. Bothara, Chandani O. Satija

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The present research work was aimed to determine stability of cefprozil monohydrate (CEFZ) as per various stress degradation conditions recommended by International Conference on Harmonization (ICH) guideline Q1A (R2). Forced degradation studies were carried out for hydrolytic, oxidative, photolytic and thermal stress conditions. The drug was found susceptible for degradation under all stress conditions. Separation was carried out by using High Performance Thin Layer Chromatographic System (HPTLC). Aluminum plates pre-coated with silica gel 60F254 were used as the stationary phase. The mobile phase consisted of ethyl acetate: acetone: methanol: water: glacial acetic acid (7.5:2.5:2.5:1.5:0.5v/v). Densitometric analysis was carried out at 280 nm. The system was found to give compact spot for cefprozil monohydrate (0.45 Rf). The linear regression analysis data showed good linear relationship in the concentration range 200-5.000 ng/band for cefprozil monohydrate. Percent recovery for the drug was found to be in the range of 98.78-101.24. Method was found to be reproducible with % relative standard deviation (%RSD) for intra- and inter-day precision to be < 1.5% over the said concentration range. The method was validated for precision, accuracy, specificity and robustness. The method has been successfully applied in the analysis of drug in tablet dosage form. Three unknown degradation products formed under various stress conditions were isolated by preparative HPTLC and characterized by mass spectroscopic studies.

Keywords: cefprozil monohydrate, degradation products, HPTLC, stress study, stability indicating method

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Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

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This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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Authors: Paulo Cumbe

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This work analyzes the economic and environmental impact of the exploitation of forest resources on populations and their sustainability in the regions where it occurs. There is an intensive and continuous activity of charcoal production, in the Massingir and Mabalane districts, in Gaza, Mozambique, to supply the most used fuel that is used by the population of the capital city, Maputo. Charcoal production is one of the sources of income for several families. However, it causes a negative environmental impact on biodiversity. We have analyzed different studies carried out in these communities that measure the speed, the level, and the impact of deforestation involving different actors, to deepen our understanding of this issue. The results of these studies reveal that the degraded area in five years would need one hundred years to be restored, which is unsustainable from an environmental point of view it is. Populations seek new areas for the same practice to maintain their livelihood, progressing with ecosystem degradation and increasing carbon dioxide emissions into the atmosphere. It is believed that environmental education, creation, and dissemination of new forms of charcoal production that are more profitable and less aggressive to the environment and forest repopulation actions need to be carried out to guarantee the sustainable development of the populations in these regions.

Keywords: deforestation, emissions, sustainability, charcoal

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Authors: Umer Ayyaz Aslam Sheikh

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Non Apis bee like the bumblebees are important due to their utilization of diverse floral plants and belong to the richest and most conspicuous flower visitors in alpine, temperate and arctic environments for pollination in both natural and managed cropping systems. These bees generally construct underground nests and habitat devastation and crumbling are major causes for their decline in nature. The present study was conducted in the Himalayan range of Azad Jammu, and Kashmir, Pakistan, surveys were conducted during the early spring season to observe maximum Bombus haemorrhoidalis queens (emerged after winter diapauses) searching for a nesting place. Whole study area was grouped into four types of landscape (open field, relatively open , relatively wooded and wooded), five habitat types (field, field boundary, pasture forest boundary and forest) and these habitat further grouped into four different patch types including withered grass, new grass, tussocks and stones and moss. Maximum nest seeking bumblebee queens preferred relatively open field landscape followed by open fields and forest boundaries. Field boundaries were recorded as most proffered habitat along with withered grasses for nesting sites of B. haemorrhoidalis queens. A wooded landscape with stone and moss type of patches were found least preferred nesting sites. This study will be helpful in the future for conservation program this for declining bumblebee species in this region. It will also provide the baseline for the conservation of other bumblebee species of the world.

Keywords: bumblebee, Bombus haemorrhoidalis, habitat, nest seeking preference, Pakistan

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Danielle Page

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Foregoing studies, statistics, and medical evaluations have established a relationship between Posttraumatic stress disorder (PTSD) and criminal justice involvement in Vietnam veterans. War is highly trauma inducing and can leave combat veterans with mental disorders ranging from psychopathic thoughts to suicidal ideation. The majority of those suffering are unaware that they have PTSD, and as a coping mechanism, they often turn to self isolation. Beyond isolation, many veterans with symptomatic PTSD turn to aggression and substance abuse to cope with their internal agony. The most common crimes committed by veterans with PTSD fall into the assault and drug/alcohol abuse categories. Thus, a relationship is established between veteran populations and the criminal justice system. This dissertation aims to define the relationship between PTSD and criminal justice involvement in veterans, explore the mediating factors in this relationship, and analyze numerous court cases in this subject area. Further, it will examine the ways in which crime rates can be reduced for veterans with symptoms of PTSD. This ranges from the improvement of healthcare systems to the implementation of special courts to handle veteran cases.

Keywords: psychotraumatology, forensic psychology, PTSD, vietnam veterans

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Authors: Miseri Roeslan Afany, Nur Ainun Pulungan

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The unique characteristics of Andisol differentiate them from other soils. These characteristics become a guideline in determining management and usage with regards to agriculture. Especially in the tropical area, Andisols may have fast mineral alteration due to intensive water movement in the soils. Four soil chemical tests were conducted for evaluating soils in the study area. Al/Fe humus, allophane, pH, and P retention were used to differentiate Andisols under different practices. Non-cultivation practice (e.g. natural forest) and cultivation practices (e.g. horticulture systems and intensive farming systems) are compared in this study. We applied Blackmore method for P retention analysis. The aims of this study are: (i) to analyze the specific behavior of Al/Fe humus, pH, and allophane towards P retention in order (ii) to evaluate the effect of cultivation practices on their behavior changes among Andisols, and (iii) to gain the sustainable agriculture through proposing an appropriate soil managements in the study area. 5 observation sites were selected, and 75 soil sampling were analyzed in this study. The results show that the cultivation decreases P retention in all sampling sites. There is a declining from ±90% to ±50% of P retention in the natural forest where shifts into cultivated land. The average of P retention under 15 years of cultivation down into 63%, whereas, the average of P retention more than 15 years of cultivation down into 54%. Many factors affect the retention of P in the soil such as: (1) type and amount of clay, (2) allophone and/or imogolit, (3) Al/Fe humus, (4) soil pH, (5) type and amount of organic material, (6) Exchangeable bases (Ca, Mg, Na, K), (7) forms and solubility of Al/Fe. To achieve the sustainable agriculture in the study area, conventional agriculture practices should be preserved and intensive fertilizing practices should be applied in order to increase the soil pH, to maintain the organic matter of andisols, to maintain microba activities, and to release Al/Fe humus complex, and thus increase available P in the soils.

Keywords: Andisols, cultivation, P retention, sustainable agriculture

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Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

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Authors: Katawut Kaewbanjong

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We analyzed a volume of data and found significant user satisfaction in software project factors. A statistical significance analysis (logistic regression) and collinearity analysis determined the significance factors from a group of 71 pre-defined factors from 191 software projects in ISBSG Release 12. The eight prediction models used for testing the prediction potential of these factors were Neural network, k-NN, Naïve Bayes, Random forest, Decision tree, Gradient boosted tree, linear regression and logistic regression prediction model. Fifteen pre-defined factors were truly significant in predicting user satisfaction, and they provided 82.71% prediction accuracy when used with a neural network prediction model. These factors were client-server, personnel changes, total defects delivered, project inactive time, industry sector, application type, development type, how methodology was acquired, development techniques, decision making process, intended market, size estimate approach, size estimate method, cost recording method, and effort estimate method. These findings may benefit software development managers considerably.

Keywords: prediction model, statistical analysis, software project, user satisfaction factor

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Authors: Adham M. Salah, Tariq A. Nagem, Raed A. Abd-Alhameed, James M. Noras

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Recently, the demand for wireless communications systems to cover more than one frequency band (multi-band) with high data rate has been increased for both fixed and mobile services. Multiple Input Multiple Output (MIMO) technology is one of the significant solutions for attaining these requirements and to achieve the maximum channel capacity of the wireless communications systems. The main issue associated with MIMO antennas especially in portable devices is the compact space between the radiating elements which leads to limit the physical separation between them. This issue exacerbates the performance of the MIMO antennas by increasing the mutual coupling between the radiating elements. In other words, the mutual coupling will be stronger if the radiating elements of the MIMO antenna are closer. This paper presents a low–profile dual-band (2×1) MIMO antenna that works at 2.4GHz, 5.3GHz and 5.8GHz for wireless local area networks (WLAN) applications. A neutralization line (NL) technique for enhancing the isolation has been used by introducing a strip line with a length of λg/4 at the isolation frequency (2.4GHz) between the radiating elements. The overall dimensions of the antenna are 33.5 x 36 x 1.6 mm³. The fabricated prototype shows a good agreement between the simulated and measured results. The antenna impedance bandwidths are 2.38–2.75 GHz and 4.4–6 GHz for the lower and upper band respectively; the reflection coefficient and mutual coupling are better than -25 dB in both lower and higher bands. The MIMO antenna performance characteristics are reported in terms of the scattering parameters, envelope correlation coefficient (ECC), total active reflection coefficient, capacity loss, antenna gain, and radiation patterns. Analysis of these characteristics indicates that the design is appropriate for the WLAN terminal applications.

Keywords: ECC, neutralization line, MIMO antenna, multi-band, mutual coupling, WLAN

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Authors: Mohammadjavad Mehrabanpour, Maryam Ranjbar Bushehri, Dorsa Mehrabanpour

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Respiratory diseases are the most important problems in the country’s poultry industry, particularly when it comes to broiler flocks. Ornithobacterium rhinotracheale (ORT) is a species that causes poor performance in growth rate, egg production, and mortality. This pathogen causes a respiratory infection including pulmonary alveolar inflammation, and pneumonia of birds throughout the world. Newcastle disease (ND) is a highly contagious disease in poultry, and also, it causes considerable losses to the poultry industry. The aim of this study was to evaluate the simultaneous occurrence of ORT and ND and NDV isolation by inoculation in embryonated eggs and confirmed by RT-PCR in broiler chicken flocks in Fars province. In this study, 318 blood and 85 tissue samples (brain, trachea, liver, and cecal tonsils) were collected from 15 broiler chicken farms. Survey serum antibody titers against ORT by using a commercial enzyme-linked immunosorbent assay (ELISA) kit performed. Evaluation of antibody titer against ND virus is performed by hemagglutination inhibition test. Virus isolation with chick embryo eggs 9-11 and RT-PCR method were carried out. A total of 318 serum samples, 135 samples (42.5%) were positive for antibodies to ORT and titer of HI antibodies against NDV in 122 serum samples (38/4%) were 7-10 (log2) and 61 serum samples (19/2%) had occurrence antibody titer against Newcastle virus and ORT. Results of the present study indicated that 20 tissue samples were positive in embryonated egg and in rapid hemagglutination (HA) test. HI test with specific ND positive serum confirmed that 6 of 20 samples. PCR confirmed that all six samples were positive and PCR products of samples indicated 535-base pair fragments in electrophrosis. Due to the great economic importance of these two diseases in the poultry industry, it is necessary to design and implement a comprehensive plan for prevention and control of these diseases.

Keywords: ELISA, Ornithobacterium rhinotracheale, newcastle disease, seroprevalence

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Maffo Maffo Nicole Liliane, Mounmeni Kpoumie Hubert, Mbaire Matindje Karl Marx, Zapfack Louis

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Sacred forests play a valuable role in conserving local biodiversity and provide numerous ecosystem services in Cameroon. The study was carried out in the sacred forests of Bandrefam and Batoufam (western Cameroon). The aim was to estimate the diversity of woody species, carbon stocks and degradation factors in these sacred forests. The floristic inventory was carried out in plots measuring 25m × 25m for trees with diameters greater than 10 cm and 5m × 5m for trees with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and the allometric equations. Data on degradation factors were collected using semi-structured surveys in the Bandrefam and Batoufam neighborhoods. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam Sacred Forest and 45 species divided into 42 genera and 27 families in the Batoufam Sacres Forest. The families common to both sacred forests are as follows: Phyllanthaceae, Fabaceae, Moraceae, Lamiaceae, Malvaceae, Rubiaceae, Meliaceae, Anacardiaceae, and Sapindaceae. Three genera are present in both sites. These are: Albizia, Macaranga, Trichillia. In addition, there are 27 species in common between the two sites. The total carbon stock is 469.26 tC/ha at Batoufam and 291.41 tC/ha at Bandrefam. The economic value varies between 15 823 877.05 fcfa at Batoufam and 9 825 530.528 fcfa at Bandrefam. The study shows that despite the sacred nature of these forests, they are subject to degradation factors such as bushfires (35.42 %), the creation of plantations (23.96 %), illegal timber exploitation (21.88 %), young people's lack of interest in the notion of conservation (9.38 %), climate change (7.29 %) and growing urbanization (2.08 %). These factors threaten biodiversity and reduce carbon storage in these forests.

Keywords: sacred forests, degradation factors, carbon stocks, semi-structured surveys

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Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt

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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.

Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone

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Authors: M. B. Abdullahi, S. M. Gumel

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This study was carried out to analyze and describe biodiversity changes in representative communities around Maladumba Lake and Forest Reserve (MLFR), Bauchi, Nigeria. Primary and secondary data were collected through formal and informal interviews of key informants and survey of local communities and government records. There has been a change in biodiversity; some of the cropping systems have become nonexistent whereas others have developed. The main aspect of the changes has been the decline of species diversity due to degradation and over utilization. The changes have also been positive through the introduction and intensification of cropping system. Options have been open for people to manipulate the cropping systems in order to efficiently use the limited resources. Farmers have opted not only to intensify agricultural practices but also to deliberately restore some of the lost species. Reduction in the number of animals per household, adoption of new techniques of land management, changes in the type of crops cultivated and intensive use of the available resources are some of the indicators describing farmers’ efforts to cope with the changes. Sustainability of the farming system and biodiversity has been enhanced through peoples’ efforts that include planting trees and use of fertilizers.

Keywords: cropping systems, historical trends, household, land management, sustainability

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Authors: Cheong Hyeon Oh, Dongho Nam, Byungsik Kim

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Due to the recent climate change, flood damage caused by local floods and typhoons has frequently occurred, the incidence rate and intensity of wildfires are greatly increased due to increased temperatures and changes in precipitation patterns. Wildfires cause primary damage, such as loss of forest resources, as well as secondary disasters, such as landslides, floods, and debris flow. In many countries around the world, damage and economic losses from secondary damage are occurring as well as the direct effects of forest fires. Therefore, in this study, the Rainfall-Runoff model(S-RAT) was used for the wildfire affected areas in Gangneung and Goseong, which occurred on April 2019, when the stability of vegetation and soil were destroyed by wildfires. Rainfall data from Typhoon Rusa were used in the S-RAT model, and flood discharge was calculated according to changes in land cover before and after wildfire damage. The results of the calculation showed that flood discharge increased significantly due to changes in land cover, as the increase in flood discharge increases the possibility of the occurrence of the debris flow and the extent of the damage, the debris flow height and range were calculated before and after forest fire using RAMMS. The analysis results showed that the height and extent of damage increased after wildfire, but the result value was underestimated due to the characteristics that using DEM and maximum flood discharge of the RAMMS model. This research was supported by a grant(2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS). This paper work (or document) was financially supported by Ministry of the Interior and Safety as 'Human resoure development Project in Disaster management'.

Keywords: wildfire, debris flow, land cover, rainfall-runoff meodel S-RAT, RAMMS, height

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Authors: Jayson Wau, David Timi, Anthony Harakuwe, Bruce Bowden, Cherie Motti, Harry Sakulas, Rag Gubag-Sipou

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The latex of F. botryocarpa fruit is applied on sores, wounds and other skin infections in Papua New Guinea ethnotherapeutic practices. Systematic bioassay guided separation and isolation of subsequent fractions of latex extracts resulted in three bioactive fractions active against Staphylococcus aureus and Escherichia coli. This study reports structural elucidation of the three isolates. Structures were determined by physical (M.pt and Rf values) and spectroscopic (1D-1H NMR, 2D-HSQC NMR, 2D-HMBC NMR) and MS ESI-POS. The two methylene protons (2H-1) and (2H-3) resonate as triplets at δ 3.59 and δ 4.99 respectively. Electron dense δ 4.99 (2H-3) on (C-3) depicts the strong electron-withdrawing component, quaternary nitrogen (=N= +). Protons resonating at δ 3.88 and 3.89 are singlets depicting two methoxy groups. Both δ 3.88 and δ 3.89 are para-aryls substituents. The methines δ 9.13 and 8.60 are singlets depicting two lone protons on the indolizidinium aryl component. All isolates, (1), (2) and (3) were identified to be ficuseptine by comparing 1D-NMR assignments. 2D-NMR and MS of (2) found it to be ficuseptine chloride '2, 3-dihydro-6, 8-bis (4-methoxyphenyl)-, 1H-indolizinium chloride'. Their counter ions of the ficuseptines were not established and provide promising lead for the further investigation.

Keywords: Ficus botryocarpa, antimicrobial activity, ficuseptine, sores

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Authors: Baali Mohamed

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Campylobacter are among the most common human bacterial gastroenteritis cases in many countries, and poultry meat is considered as a major source of human campylobacteriosis. This study is conducted, on one hand, to determine the prevalence of infection with thermotolerant Campylobacter both in broiler flocks and men, and to study their sensitivity to antibiotics, and secondly for comparing the two methods of isolation of Campylobacter thermotolerant: technique of passive filtration and selective isolation technique using the Karmali medium. This study examined 310 samples, 260 of avian origin and 50 of human origin, during the period from June 2011 to March 2012. Detecting Campylobacter thermotolerant is conducted using the standard ISO 10272. The results show that 66% (95% CI : 60-72%) of avian samples are contaminated with C. TT (172/260). The study of antibiotic susceptibility revealed that all strains (100%) are resistant to ampicillin and amoxicillin/clavulanic acid, 90% to erythromycin, 66.3% to tetracycline, 53.3% to chloramphenicol and 46.7% to enrofloxacin. However, no resistance is noted to gentamycin. In human samples, three strains of C. thermotolerant are detected, with a contamination rate of 6%. The results of the statistical analysis using the chi-square test (χ2) showed that Campylobacter infection, on the one hand, had seasonal variation with a summer peak (p < 0.05) and, on the other hand, are not influenced by the size of the herd.

Keywords: thermotolerant campylobacter, broiler, man, Karmali

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Authors: Mohammadreza Azarnoush, Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considers the consumption of fossil fuels and also reduction of consumption civil energy in megacities as playing a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming, and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials, and the adoption to the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article, we investigate the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

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Authors: Tsai-Hsiu Lin

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Three dimensions of teacher culture hinder educational improvement: individualism, conservatism and presentism. To promote the professional development of teachers, these three aspects in teacher culture should be eliminated. Classroom observation may be a useful method of eliminating individualism. The Ministry of Education in Taiwan has attempted to reduce the isolation of teachers to promote their professional growth. Because classroom observation discourse varies, teachers are generally unwilling to allow their teaching to be observed. However, classroom observations take place in the country in the form of school evaluations. The main purpose of this study was to explore the differences in teachers’ conservatism, individualism and presentism after classroom observations had been conducted at an elementary school in Taiwan. The research method was a qualitative case study involving interviews with the school principal, the director of academic affairs, and two classroom teachers. The following conclusions were drawn: (1) Educators in different positions viewed classroom observations differently; (2) The classroom teachers did not highly value classroom observation; (3) There was little change in the teachers’ conservatism, individualism and presentism after classroom observation.

Keywords: classroom observation, Lortie’s Trinity, teacher culture, teacher professional development

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Oluwatobi Emmanuel Olaniyi, Babafemi George Ogunjemite

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The high rate of infrastructural development in Ikogosi warm spring towards harnessing her great ecotourism potentials calls for a serious concern, as more forest areas are been opened up for public access and the landscape is modified. On this note, we investigated the implication of ecotourism development on the floristic composition and forest structure in Ikogosi. The study aimed at identifying the past and present status of infrastructural development, assessing and comparing the floristic composition and structure of the built- up/ recreational areas and undisturbed forested areas, to infer on the impact of ecotourism development on the study site. We conducted stakeholder interview and field observation to identify the past and present status of infrastructural development respectively. A total of ten quadrants were employed in the vegetation assessment to characterize the woody tree species composition, diameter at breast height and height, to obtain mean indices characterizing each part of the site. These indices were compared using T – test analysis. A total of 49 different woody tree species distributed in 21 families were identified in the built-in/ recreational areas while 67 different woody tree species belonging to 25 families were recorded in the undeveloped forested areas. Although, the latter has a higher mean diameter at breast height of woody trees, it was not significantly different from the former (T-test = -0.74, p = 0.46). On the contrary, the built-up area had a higher mean trees height than the undeveloped areas, but the difference was not statistically significant (T-test= 1.04, p = 0.30). Despite these, the slight reduction in richness and diversity of the woody tree species in the built- up/ recreational areas implies mitigating the negative effects of infrastructural development on the warm spring's vegetation.

Keywords: ecosystem services, forest structure, vegetation assessment, warm-spring

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: S. Rostampour Yasouri, M. Ghane

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Leptospirosis is one the most important common diseases between human and live stock occurred by different species of Leptospira. This disease has been construed as the native in the northern provinces of Iran and risk of the infection with pathogenic is high. One hundred fifteen samples of water (67), soil (36) and feces of rodents (12) were collected from the rice fields of the suburbs of Tonekabon Township situated in northern part of Iran in 2012. The samples, after passage from membranous filters, were cultured in the liquid and solid EMJH medium and incubated at 30°C for 1 month. Leptospira spp. were isolated using culture technique, and the plates were studied from viewpoint of colony formation, microscopic observations and then identified by phenotyping tests. Finally, the identification of Leptospira genus was verified by PCR technique and 16S rRNA gene sequencing. Of 115 samples totally, 55 samples (47.82%) became positive by use of the culture technique which the positive cases included 47 water samples (70.14%) and 8 soil samples (22.22%), while the isolation was not accomplished from the sample of the rodents feces. Overall, according to these data, Leptospira spp. exists with high frequency in North Iran. Hence, based on foregoing evidence environments in the north of Iran are vehicles of Leptospira spp.

Keywords: EMJH Medium, Leptospira, Northern of Iran, rice fields

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Authors: Xiaoqing Liu, Kurt Friese, Karsten Rinke

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Lacustrine sediment archives rich paleoenvironmental information in lake and surrounding environment. Additionally, modern sediment is used as an effective medium for the monitoring of lake. Organic carbon in sediment is a heterogeneous mixture with varying turnover times and qualities which result from the different biogeochemical processes in the deposition of organic material. Therefore, the isolation of different carbon pools is important for the research of lacustrine condition in the lake. However, the numeric available fractionation procedures can hardly yield homogeneous carbon pools on terms of stability and age. In this work, a multi-step fractionation protocol that treated sediment with hot water, HCl, H2O2 and Na2S2O8 in sequence was adopted, the treated sediment from each step were analyzed for the isotopic and structural compositions with Isotope Ratio Mass Spectrometer coupled with element analyzer (IRMS-EA) and Solid-state 13C Nuclear Magnetic Resonance (NMR), respectively. The sequential extractions with hot-water, HCl, and H2O2 yielded a more homogeneous and C3 plant-originating OC fraction, which was characterized with an atomic C/N ratio shift from 12.0 to 20.8, and 13C and 15N isotopic signatures were 0.9‰ and 1.9‰ more depleted than the original bulk sediment, respectively. Additionally, the H2O2- resistant residue was dominated with stable components, such as the lignins, waxes, cutans, tannins, steroids and aliphatic proteins and complex carbohydrates. 6M HCl in the acid hydrolysis step was much more effective than 1M HCl to isolate a sedimentary OC fraction with higher degree of homogeneity. Owing to the extremely high removal rate of organic matter, the step of a Na2S2O8 oxidation is only suggested if the isolation of the most refractory OC pool is mandatory. We conclude that this multi-step chemical fractionation procedure is effective to isolate more homogeneous OC pools in terms of stability and functional structure, and it can be used as a promising method for OC pools fractionation of sediment or soil in future lake research.

Keywords: 13C-CPMAS-NMR, 13C signature, lake sediment, OC fractionation

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