Search results for: conservation of forest

Authors: Abhishek Srivastava, Jeevesh Nandan, Manish Kumar

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The study was taken to analyse the alternative source of traffic system for effective and more convenient traffic flow by reducing points of conflicts as well as angle of conflict and keeping in view to minimize the problem of unnecessarily long waiting time, delays, congestion, traffic jam and geometric delays due to intersection between circular and straight lanes. It is a twin kidney-spine type structure system with special allowance for Highway users for quicker passes. Thus reduction in number and intensity of accidents, significance reduction in traffic jam, conservation of valuable time.

Keywords: traffic system, collision reduction of vehicles, smooth flow of vehicles, traffic jam

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Authors: Tsegaw Abebe, Temesgen Abebe

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Land degradation is one of a serious environmental challenge in Ethiopia and is one of the major underlying causes for declining agricultural productivity. The Ethiopia government realized the significance of environmental restoration specifically on deforested and degraded land after the 1973 and 1984/85 major famines that struck the country. Among the various conservation strategies, the establishment of area exclosures have been regarded as an effective response to halt and reverse the problems of land degradation. There are limited studies in Ethiopia dealing how the conversion of free grazing lands and degraded lands by closures increase biomass accumulation. However, these studies are not sufficient to conclude about the strength of area closures to restore degraded vegetations at the diverse agro-ecological condition. The overall objective of this study was, therefore, to assess and evaluate the usefulness of area closure technique in enhancing rehabilitation of degraded ecosystem and thereby increase the natural capital in the study site (southern Ethiopia). Woody plant species were collected from area exclosure for eight year and adjacent degraded land with similar landscape positions using systematic sampling plot design technique. Woody species diversity was determined by Shannon diversity. Comparative assessment result of woody plant species analysis showed that the density of woody species in the exclosure and degraded site were 778 and 222 individuals per hectare, respectively. A total of 16 woody species, representing 12 families were recorded in the study site. Out of the 12 families, all were recorded in the exclosure while 5 were recorded in the degraded site. Out of the 16 species, 15 were recorded in the exclosure while six were in the degraded site. A total of 10 species were recorded in the exclosure, which were absent in the degraded site. Similarly, one species was recorded in the degraded site which was not present in the exclosure. The results showed that protecting of degraded site from human and animal disturbances promotes woody plant species regenerations and productivity Apart from increasing woody plant species, the local communities have benefited from the exclosure in the form of both products (grass harvesting) and services (ecological). Due to this reason the local communities have positive attitudes and contribute a lot for the success of enclosures in the study site. The present study clearly showed that area closure interventions should be oriented towards managing and improving the productivity of the degraded land, in such a way that both the need for conservation of biodiversity and environmental sustainability, and the demands of the local people for biomass resources can be achieved.

Keywords: degraded land, exclosure, land restoration, woody vegetation

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Authors: Stamatia Nasiakou, Dimitrios Chouvardas, Michael Vrahnakis, Vassiliki Kleftoyanni

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Recent research in the mountainous and semi-mountainous rural landscapes of Greece shows that they have been significantly changed over the last 80 years. These changes have the form of structural modification of land cover/use patterns, with the main characteristic being the extensive expansion of dense forests and shrubs at the expense of grasslands and extensive agricultural areas. The aim of this research was to study the 60-year changes (1960-2019) of land cover/ use units in the rural landscape of Mouzaki (Karditsa Prefecture, central Greece). Relevant cartographic material such as forest land use maps, digital maps (Corine Land Cover -2018), 1960 aerial photos from Hellenic Military Geographical Service, and satellite imagery (Google Earth Pro 2014, 2016, 2017 and 2019) was collected and processed in order to study landscape evolution. ArcGIS v 10.2.2 software was used to process the cartographic material and to produce several sets of data. Main product of the analysis was a digitized photo-mosaic of the 1960 aerial photographs, a digitized photo-mosaic of recent satellite images (2014, 2016, 2017 and 2019), and diagrams and maps of temporal transformation of the rural landscape (1960 – 2019). Maps and diagrams were produced by applying photointerpretation techniques and a suitable land cover/ use classification system on the two photo-mosaics. Demographic and socioeconomic inventory data was also collected mainly from diachronic census reports of the Hellenic Statistical Authority and local sources. Data analysis of the temporal transformation of land cover/ use units showed that they are mainly located in the central and south-eastern part of the study area, which mainly includes the mountainous part of the landscape. The most significant change is the expansion of the dense forests that currently dominate the southern and eastern part of the landscape. In conclusion, the produced diagrams and maps of the land cover/ use evolution suggest that woody vegetation in the rural landscape of Mouzaki has significantly increased over the past 60 years at the expense of the open areas, especially grasslands and agricultural areas. Demographic changes, land abandonment and the transformation of traditional farming practices (e.g. agroforestry) were recognized as the main cause of the landscape change. This study is part of a broader research project entitled “Perspective of Agroforestry in Thessaly region: A research on social, environmental and economic aspects to enhance farmer participation”. The project is funded by the General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI).

Keywords: Agroforestry, Forest expansion, Land cover/ use changes, Mountainous and semi-mountainous areas

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Authors: Carlos Teodoro, Oscar Bautista

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In this work, we analyze theoretically the mass transport in a time-periodic electroosmotic flow through a parallel flat plate microchannel under different periodic functions of the applied external electric field. The microchannel connects two reservoirs having different constant concentrations of an electro-neutral solute, and the zeta potential of the microchannel walls are assumed to be uniform. The governing equations that allow determining the mass transport in the microchannel are given by the Poisson-Boltzmann equation, the modified Navier-Stokes equations, where the Debye-Hückel approximation is considered (the zeta potential is less than 25 mV), and the species conservation. These equations are nondimensionalized and four dimensionless parameters appear which control the mass transport phenomenon. In this sense, these parameters are an angular Reynolds, the Schmidt and the Péclet numbers, and an electrokinetic parameter representing the ratio of the half-height of the microchannel to the Debye length. To solve the mathematical model, first, the electric potential is determined from the Poisson-Boltzmann equation, which allows determining the electric force for various periodic functions of the external electric field expressed as Fourier series. In particular, three different excitation wave forms of the external electric field are assumed, a) sawteeth, b) step, and c) a periodic irregular functions. The periodic electric forces are substituted in the modified Navier-Stokes equations, and the hydrodynamic field is derived for each case of the electric force. From the obtained velocity fields, the species conservation equation is solved and the concentration fields are found. Numerical calculations were done by considering several binary systems where two dilute species are transported in the presence of a carrier. It is observed that there are different angular frequencies of the imposed external electric signal where the total mass transport of each species is the same, independently of the molecular diffusion coefficient. These frequencies are called crossover frequencies and are obtained graphically at the intersection when the total mass transport is plotted against the imposed frequency. The crossover frequencies are different depending on the Schmidt number, the electrokinetic parameter, the angular Reynolds number, and on the type of signal of the external electric field. It is demonstrated that the mass transport through the microchannel is strongly dependent on the modulation frequency of the applied particular alternating electric field. Possible extensions of the analysis to more complicated pulsation profiles are also outlined.

Keywords: electroosmotic flow, mass transport, oscillatory flow, species separation

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Authors: Hatice Esra Akgül, Celaleddin Öztürk

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Lichen biodiversity in forests is controlled by environmental conditions. Epiphytic lichens have some degree of substrate specificity. Diversity and distribution of epiphytic lichens are affected by humidity, light, altitude, temperature, bark pH of the trees.This study describes the epiphytic lichen communities with comparing their preferred tree species. 34 epiphytic lichen taxa are reported on Pinus sp. L., Quercus sp. L., Fagus sp. L., Carpinus sp. L., Abies sp. Mill., Fraxinus sp. Tourn. ex L. from different altitudes around the Şeker Canyon (Karabük, Turkey). 11 of these taxa are growing on Quercus sp., 10 of them are growing on Fagus sp., 7 of them are growing on Pinus sp., 4 of them are on Carpinus sp., 2 of them are on Abies sp. and one of them is on Fraxinus sp. Evernia prunastri (L.) Ach. is growing on both of Fagus sp. and Quercus sp. Lecanora pulicaris (Pers.) Ach. is growing on both of Abies sp. and Quercus sp.

Keywords: biodiversity, epiphytic lichen, forest, Turkey

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Authors: Harald Lindorfer, Bettina Frauz, Dietmar Ramhold

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Next to the well-known inhibitors in anaerobic digestion like ammonia, antibiotics or disinfectants, the number of process failures connected with mould growth in the feedstock increased significantly in the last years. It was assumed that mycotoxins are the cause of the negative effects. The financial damage to plants associated with these process failures is considerable. The aim of this study was to find a way of predicting the failures and furthermore strategies for a fast process recovery. In a first step, mould-contaminated feedstocks causing process failures in full-scale digesters were sampled and analysed on mycotoxin content. A selection of these samples was applied to biological inhibition tests. In this test, crystalline cellulose is applied in addition to the feedstock sample as standard substrate. Affected digesters were also sampled and analytical process data as well as operational data of the plants were recorded. Additionally, different mycotoxin substances, Deoxynivalenol, Zearalenon, Aflatoxin B1, Mycophenolic acid and Citrinin, were applied as pure substances to lab-scale digesters, individually and in various combinations, and effects were monitored. As expected, various mycotoxins were detected in all of the mould-contaminated samples. Nevertheless, inhibition effects were observed with only one of the collected samples, after applying it to an inhibition test. With this sample, the biogas yield of the standard substrate was reduced by approx. 20%. This result corresponds with observations made on full-scale plants. However, none of the tested mycotoxins applied as pure substance caused a negative effect on biogas production in lab scale digesters, neither after application as individual substance nor in combination. The recording of the process data in full-scale plants affected by process failures in most cases showed a severe accumulation of fatty acids alongside a decrease in biogas production and methane concentration. In the analytical data of the digester samples, a typical distribution of fatty acids with exceptionally high acetic acid concentrations could be identified. This typical fatty acid pattern can be used as a rapid identification parameter pointing to the cause of the process troubles and enable a fast implication of countermeasures. The results of the study show that more attention needs to be paid to feedstock storage and feedstock conservation before their application to anaerobic digesters. This is all the more important since first studies indicate that the occurrence of mycotoxins will likely increase in Europe due to the ongoing climate change.

Keywords: Anaerobic digestion, Biogas, Feedstock conservation, Fungal mycotoxins, Inhibition, process failure

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Sukrat Sinha, Abhay Kumar, Shanthy Sundaram

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The Leishmania homologue of activated C kinase (LACK) is known T cell epitope from soluble Leishmania antigens (SLA) that confers protection against Leishmania challenge. This antigen has been found to be highly conserved among Leishmania strains. LACK has been shown to be protective against L. donovani challenge. A comprehensive analysis of several LACK sequences was completed. The analysis shows a high level of conservation, lower variability and higher antigenicity in specific portions of the LACK protein. This information provides insights for the potential consideration of LACK as a putative candidate in the context of visceral Leishmaniasis vaccine target.

Keywords: bioinformatics, genome assembly, leishmania activated protein kinase c (lack), next-generation sequencing

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Authors: Nicola S. Schutte, John M. Malouff

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Introduction: Curiosity is a positive emotion and motivational state that consists of the desire to know. Curiosity consists of several related dimensions, including a desire for exploration, deprivation sensitivity, and stress tolerance. Creativity involves generating novel and valuable ideas or products. How curiosity may prompt greater creativity remains to be investigated. The phenomena of flow may link curiosity and creativity. Flow is characterized by intense concentration and absorption and gives rise to optimal performance. Objective of Study: The objective of the present study was to investigate whether the phenomenon of flow may link curiosity with creativity. Methods and Design: Fifty-seven individuals from Australia (45 women and 12 men, mean age of 35.33, SD=9.4) participated. Participants were asked to design a program encouraging residents in a local community to conserve water and to record the elements of their program in writing. Participants were then asked to rate their experience as they developed and wrote about their program. Participants rated their experience on the Dimensional Curiosity Measure sub-scales assessing the exploration, deprivation sensitivity, and stress tolerance facets of curiosity, and the Flow Short Scale. Reliability of the measures as assessed by Cronbach's alpha was as follows: Exploration Curiosity =.92, Deprivation Sensitivity Curiosity =.66, Stress Tolerance Curiosity =.93, and Flow=.96. Two raters independently coded each participant’s water conservation program description on creativity. The mixed-model intraclass correlation coefficient for the two sets of ratings was .73. The mean of the two ratings produced the final creativity score for each participant. Results: During the experience of designing the program, all three types of curiosity were significantly associated with the flow. Pearson r correlations were as follows: Exploration Curiosity and flow, r =.68 (higher Exploration Curiosity was associated with more flow); Deprivation Sensitivity Curiosity and flow, r =.39 (higher Deprivation Sensitivity Curiosity was associated with more flow); and Stress Tolerance Curiosity and flow, r = .44 (more stress tolerance in relation to novelty and exploration was associated with more flow). Greater experience of flow was significantly associated with greater creativity in designing the water conservation program, r =.39. The associations between dimensions of curiosity and creativity did not reach significance. Even though the direct relationships between dimensions of curiosity and creativity were not significant, indirect relationships through the mediating effect of the experience of flow between dimensions of curiosity and creativity were significant. Mediation analysis using PROCESS showed that flow linked Exploration Curiosity with creativity, standardized beta=.23, 95%CI [.02,.25] for the indirect effect; Deprivation Sensitivity Curiosity with creativity, standardized beta=.14, 95%CI [.04,.29] for the indirect effect; and Stress Tolerance Curiosity with creativity, standardized beta=.13, 95%CI [.02,.27] for the indirect effect. Conclusions: When engaging in an activity, higher levels of curiosity are associated with greater flow. More flow is associated with higher levels of creativity. Programs intended to increase flow or creativity might build on these findings and also explore causal relationships.

Keywords: creativity, curiosity, flow, motivation

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Authors: Diamant Irene, Dar Tamar

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Burnout, conceptualized within the framework of stress research, is to a large extent a result of a threat on resources of time or a feeling of time shortage. In reaction to numerous tasks, deadlines, high output, management of different duties encompassing work-home conflicts, many individuals experience ‘time pressure’. Time pressure is characterized as the perception of a lack of available time in relation to the amount of workload. It can be a result of local objective constraints, but it can also be a chronic attribute in coping with life. As such, time pressure is associated in the literature with general stress experience and can therefore be a direct, contributory burnout factor. The present study examines the relation of chronic time pressure – feeling of time shortage and of being rushed, with another central aspect in subjective temporal experience - time perspective. Time perspective is a stable personal disposition, capturing the extent to which people subjectively remember the past, live the present and\or anticipate the future. Based on Hobfoll’s Conservation of Resources Theory, it was hypothesized that individuals with chronic time pressure would experience a permanent threat on their time resources resulting in relatively increased burnout. In addition, it was hypothesized that different time perspective profiles, based on Zimbardo’s typology of five dimensions – Past Positive, Past Negative, Present Hedonistic, Present Fatalistic, and Future, would be related to different magnitudes of chronic time pressure and of burnout. We expected that individuals with ‘Past Negative’ or ‘Present Fatalist’ time perspectives would experience more burnout, with chronic time pressure being a moderator variable. Conversely, individuals with a ‘Present Hedonistic’ - with little concern with the future consequences of actions, would experience less chronic time pressure and less burnout. Another temporal experience angle examined in this study is the difference between the actual distribution of time (as in a typical day) versus desired distribution of time (such as would have been distributed optimally during a day). It was hypothesized that there would be a positive correlation between the gap between these time distributions and chronic time pressure and burnout. Data was collected through an online self-reporting survey distributed on social networks, with 240 participants (aged 21-65) recruited through convenience and snowball sampling methods from various organizational sectors. The results of the present study support the hypotheses and constitute a basis for future debate regarding the elements of burnout in the modern work environment, with an emphasis on subjective temporal experience. Our findings point to the importance of chronic and stable temporal experiences, as time pressure and time perspective, in occupational experience. The findings are also discussed with a view to the development of practical methods of burnout prevention.

Keywords: conservation of resources, burnout, time pressure, time perspective

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Authors: Hari O. Saxena, Ganesh

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In the present investigation, chemical fingerprints of methanolic extracts of roots, stem and leaves of Uraria picta were developed using HPTLC technique. These fingerprints will be useful for authentication as well as in differentiating the species from adulterants. These will also serve as a biochemical marker for this valuable species in pharmaceutical industries and plant systemic studies. Roots, stem and leaves of Uraria picta were further evaluated for quantification of an active ingredient lupeol to find out alternatives to roots. Results showed more content of lupeol in stem (0.048%, dry wt.) as compare to roots (0.017%, dry wt.) suggesting the utilization of stem in place of roots. It will avoid uprooting of this prestigious plant which ultimately will promote its conservation.

Keywords: chemical fingerprints, lupeol, quantification, Uraria picta

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Authors: Kenneth Lee

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During Buddha’s time in the 5th century BCE, the Indian society was organized by a social stratification system called “the caste system” (Skt. varna), which still exists today. The origination of the caste system can be traced back to 1500 BCE within the ancient Vedic texts of the Aryans, the Indo-European nomadic people who migrated and settled in the Indus Valley region. However, the four-tiered hierarchical nature of the caste system created inequality, privilege, and discrimination based on hereditary transmission. After renouncing his royal status as a prince, Siddhartha Gautama spent six years in the forest, practiced austerities, mastered meditation, and eventually realized enlightenment. Thereupon, now referred to as “Shakyamuni Buddha” or “sage from the tribe of Shakya who has become awake,” the Buddha founded the Sangha, a community of monks, nuns, and lay followers, where everyone was equal and treated equally. After providing a brief overview of Buddha’s time, this talk will examine Buddha’s Dharma or teachings on equality and his creation of the Sangha as “society within a society, which had a dissolving effect on society.

Keywords: equality, women, buddhism, discrimination

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Authors: Juan Heredia, Naci Dilekli

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The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

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Authors: Timothy Garvey, Don Driscoll

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Within Tasmania, the growling grass frog (Litoria raniformis) has experienced a rapid contraction in distribution. This decline is primarily attributed to habitat loss through landscape modification and improved land drainage. Reductions in seasonal water-sources have placed increasing importance on permanent water bodies for reproduction and foraging. Tasmanian agricultural and commercial forestry landscapes often feature small artificial ponds, utilized for watering livestock and fighting wildfires. Improved knowledge of how L. raniformis may be exploiting anthropogenic ponds is required for improved conservation management. We implemented telemetric tracking in order to evaluate the spatial ecology of L. raniformis (n = 20) within agricultural and managed forestry sites, with tracking conducted periodically over the breeding season (November/December, January/February, March/April). We investigated (1) potential differences in habitat utilization between agricultural and plantation sites, and (2) the post-breeding dispersal of individual frogs. Frogs were found to remain in close proximity to ponds throughout November/December, with individuals occupying vegetative depauperate water bodies beginning to disperse by January/February. Dispersing individuals traversed exposed plantation understory and agricultural pasture land in order to enter patches of native scrubland. By March/April all individuals captured at minimally vegetated ponds had retreated to adjacent scrub corridors. Animals found in ponds featuring dense riparian vegetation were not recorded to disperse. No difference in behavior was recorded between sexes. Rising temperatures coincided with increased movement by individuals towards native scrub refugia. The patterns of movement reported in this investigation emphasize the significant contribution of manmade water-bodies towards the conservation of L. raniformis within modified landscapes. The use of natural scrubland as cyclical retreats between breeding seasons also highlights the importance of the continued preservation of remnant vegetation corridors. Loss of artificial dams or buffering scrubland in heavily altered landscapes could see the breakdown of the greater L. raniformis meta-population further threatening their regional persistence.

Keywords: habitat loss, modified landscapes, spatial ecology, telemetry

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Authors: Mohamed Elshobaki, Alessandro Valiani, Valerio Caleffi

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In this paper, we solve 1-D shallow water equation for sub-critical and super-critical water flow at junction. The water flow at junction has been studied for the last 50 years from the physical-hydraulic point of views and for numerical computations need more attention. For numerical simulation, we need to establish an inner boundary condition at the junction to avoid an oscillation which rise from the waves interactions at the junction. Indeed, we introduce a new boundary condition at the junction based on the mass conservation, total head, and the admissible wave relations between the flow parameters in the three branches to predict the water depths and discharges at the junction. These boundary conditions are valid for sub-critical flow and super-critical flow.

Keywords: numerical simulation, junction flow, sub-critical flow, super-critical flow

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Zakeia Benmoussa

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Pressure on freshwater systems comes from removing too much water to grow crops; contamination from economic activities, land use practices, and human waste. The paper will be focusing on how water management can influence the design, implementation, and impacts of the ecological principles of biomimicry as sustainable methods in recycling wastewater. At Texas State, United States of America, in particular the lower area of the Trinity River refuge, there is a true example of the diversity to be found in that area, whether when exploring the lands or the waterways. However, as the Trinity River supplies water to the state’s residents, the lower part of the river at Liberty County presents several problem of wastewater discharge in the river. Therefore, conservation efforts are particularly important in the Trinity River basin. Clearly, alternative ways must be considered in order to conserve water to meet future demands. As a result, there should be another system provided rather than the conventional water treatment. Mimicking ecosystem's technologies out of context is not enough, but if we incorporate plants into building architecture, in addition to their beauty, they can filter waste, absorb excess water, and purify air. By providing an architectural proposal center, a living system can be explored through several methods that influence natural resources on the micro-scale in order to impact sustainability on the macro-scale. The center consists of an ecological program of Plant and Water Biomimicry study which becomes a living organism that purifies the river water in a natural way through architecture. Consequently, a rich beautiful nature could be used as an educational destination, observation and adventure, as well as providing unpolluted fresh water to the major cities of Texas. As a result, these facts raise a couple of questions: Why is conservation so rarely practiced by those who must extract a living from the land? Are we sufficiently enlightened to realize that we must now challenge that dogma? Do architects respond to the environment and reflect on it in the correct way through their public projects? The method adopted in this paper consists of general research into careful study of the system of the living machine, in how to integrate it at architectural level, and finally, the consolidation of the all the conclusions formed into design proposal. To summarise, this paper attempts to provide a sustainable alternative perspective in bridging physical and mental interaction with biodiversity to enhance nature by using architecture.

Keywords: Biodiversity, Design with Nature, Sustainable architecture, Waste water treatment.

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Authors: N. E. F. Jaddil, S. Silang, J. H. Chong

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Semenggoh Wildlife Centre (SWC) begins its journey as an important orangutan rehabilitation centre in Sarawak. Strategically located about 25 km from Kuching, the capital city of Malaysian Sarawak in Borneo Island. This paper sought to access the progression of Semenggoh Wildlife Centre from a rehabilitation into one of the top ecotourism destination in Kuching. The existing semi-wild orangutans (attraction)-ecotourism interaction in city landscape setting is evaluated. With the ever-increasing demand of ecotourism activity in SWC, this study is intended to explore and understand the current status of ecotourism activity in SWC by analysing visitors, and economic statistic, issues and challenges and strategically propose way-forward to enhance the sustainability of ecotourism in SWC.

Keywords: ecotourism, orangutan, Semenggoh, urban wildlife park

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Authors: S. O. Oyamakin, A. U. Chukwu

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Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Anugrah Tripathi, H. S. Ginwal, Charul Kainthola

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Bamboos are considered as valuable resources which have the potential of meeting current economic, environmental and social needs. Bamboo has played a key role in humankind and its livelihood since ancient time. Distributed in diverse areas across the globe, bamboo makes an important natural resource for hundreds of millions of people across the world. In some of the Asian countries and northeast part of India, bamboo is the basis of life on many horizons. India possesses the largest bamboo-bearing area across the world and a great extent of species richness, but this rich genetic resource and its diversity have dwindled in the natural forest due to forest fire, over exploitation, lack of proper management policies, and gregarious flowering behavior. Bamboos which are well known for their peculiar, extraordinary morphology, show a lot of variation in many scales. Among the various bamboo species, Dendrocalamus strictus is the most abundant bamboo resource in India, which is a deciduous, solid, and densely tufted bamboo. This species can thrive in wide gradients of geographical as well as climatic conditions. Due to this, it exhibits a significant amount of variation among the populations of different origins for numerous morphological features. Morphological parameters are the front-line criteria for the selection and improvement of any forestry species. Study on the diversity among eight important morphological characters of D. strictus was carried out, covering 16 populations from wide geographical locations of India following INBAR standards. Among studied 16 populations, three populations viz. DS06 (Gaya, Bihar), DS15 (Mirzapur, Uttar Pradesh), and DS16 (Bhogpur, Pinjore, Haryana) were found as superior populations with higher mean values for parametric characters (clump height, no. of culms/ clump, circumference of clump, internode diameter and internode length) and with the higher sum of ranks in non-parametric characters (straightness, disease, and pest incidence and branching pattern). All of these parameters showed an ample amount of variations among the studied populations and revealed a significant difference among the populations. Variation in morphological characters is very common in a species having wide distribution and is usually evident at various levels, viz., between and within the populations. They are of paramount importance for growth, biomass, and quick production gains. Present study also gives an idea for the selection of the population on the basis of these morphological parameters. From this study on morphological parameters and their variation, we may find an overview of best-performing populations for growth and biomass accumulation. Some of the studied parameters also provide ideas to standardize mechanisms of selecting and sustainable harvesting of the clumps by applying simpler silvicultural systems so that they can be properly managed in homestead gardens for the community utilization as well as by commercial growers to meet the requirement of industries and other stakeholders.

Keywords: Dendrocalamus strictus, homestead garden, gregarious flowering, stakeholders, INBAR

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale, Rubens Maribondo do Nascimento, José Ubiragi de Lima Mendes

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Given the unquestionable need of environmental preservation of discarded industrial residues, The scrape of tires have been seen as a salutary alternative for addictive in concrete, asphalt production and of other composites materials. In this work, grew a composite the base of scrape of tire as reinforcement and latex as matrix, to be used as insulating thermal in "cold" systems (0º). Analyzed the acting of the material was what plays the thermal conservation when submitted the flow of heat. Verified the temperature profiles in the internal surfaces and it expresses of the composite as well as the temperature gradient in the same. As a consequence, in function of the answers of the system, conclusions were reached.

Keywords: cold system, latex, flow of heat, asphalt production

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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Authors: Shigeyuki Haruyama, Ken Kaminishi, Junji Kaneko, Tadayuki Kyoutani, Siti Ruhana Omar, Oke Oktavianty

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This study is used as a definition method to the value and function in manufacturing sector. In concurrence of discussion about present condition of modeling method, until now definition of 1D-CAE is ambiguity and not conceptual. Across all the physics fields, those methods are defined with the formulation of differential algebraic equation which only applied time derivation and simulation. At the same time, we propose semi-acausal modeling concept and differential algebraic equation method as a newly modeling method which the efficiency has been verified through the comparison of numerical analysis result between the semi-acausal modeling calculation and FEM theory calculation.

Keywords: system model, physical models, empirical models, conservation law, differential algebraic equation, object-oriented

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Authors: Charlotte K. Lee, Henrique R. N. Aguiar, Ralph Smith, James Baldock, Sam Botchey

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Background: Femoral neck stress fractures (FNSF) are uncommon, making up 1 to 7.2% of stress fractures in healthy subjects. FNSFs are prevalent in young women, military recruits, endurance athletes, and individuals with energy deficiency syndrome or female athlete triad. Presentation is often non-specific and is often misdiagnosed following the initial examination. There is limited research addressing the return–to–activity time after FNSF. Previous studies have demonstrated prognostic time predictions based on various imaging techniques. Here, (1) OxSport clinic FNSF practice standards are retrospectively reviewed, (2) FNSF cohort demographics are examined, (3) Regression models were used to predict return–to–activity prognosis and consequently determine bone stress risk factors. Methods: Patients with a diagnosis of FNSF attending Oxsport clinic between 01/06/2020 and 01/01/2020 were selected from the Rheumatology Assessment Database Innovation in Oxford (RhADiOn) and OxSport Stress Fracture Database (n = 14). (1) Clinical practice was audited against five criteria based on local and National Institute for Health Care Excellence guidance, with a 100% standard. (2) Demographics of the FNSF cohort were examined with Student’s T-Test. (3) Lastly, linear regression and Random Forest regression models were used on this patient cohort to predict return–to–activity time. Consequently, an analysis of feature importance was conducted after fitting each model. Results: OxSport clinical practice met standard (100%) in 3/5 criteria. The criteria not met were patient waiting times and documentation of all bone stress risk factors. Importantly, analysis of patient demographics showed that of the population with complete bone stress risk factor assessments, 53% were positive for modifiable bone stress risk factors. Lastly, linear regression analysis was utilized to identify demographic factors that predicted return–to–activity time [R2 = 79.172%; average error 0.226]. This analysis identified four key variables that predicted return-to-activity time: vitamin D level, total hip DEXA T value, femoral neck DEXA T value, and history of an eating disorder/disordered eating. Furthermore, random forest regression models were employed for this task [R2 = 97.805%; average error 0.024]. Analysis of the importance of each feature again identified a set of 4 variables, 3 of which matched with the linear regression analysis (vitamin D level, total hip DEXA T value, and femoral neck DEXA T value) and the fourth: age. Conclusion: OxSport clinical practice could be improved by more comprehensively evaluating bone stress risk factors. The importance of this evaluation is demonstrated by the population found positive for these risk factors. Using this cohort, potential bone stress risk factors that significantly impacted return-to-activity prognosis were predicted using regression models.

Keywords: eating disorder, bone stress risk factor, femoral neck stress fracture, vitamin D

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana

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Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.

Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning

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Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: N. Moazami, R. Ranjbar, A. Ashori

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Out of hundreds of microalgal strains reported, only very few of them are capable for production of high content of lipid. Therefore, the key technical challenges include identifying the strains with the highest growth rates and oil contents with adequate composition, which were the main aims of this work. From 147 microalgae screened for high biomass and oil productivity, the Nannochloropsis sp. PTCC 6016, which attained 52% lipid content, was selected for large scale cultivation in Persian Gulf Knowledge Island. Nannochloropsis strain PTCC 6016 belongs to Eustigmatophyceae (Phylum heterokontophyta) isolated from Mangrove forest area of Qheshm Island and Persian Gulf (Iran) in 2008. The strain PTCC 6016 had an average biomass productivity of 2.83 g/L/day and 52% lipid content. The biomass productivity and the oil production potential could be projected to be more than 200 tons biomass and 100000 L oil per hectare per year, in an outdoor algal culture (300 day/year) in the Persian Gulf climate.

Keywords: biofuels, microalgae, Nannochloropsis, raceway open pond, bio-jet

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