Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Hydraulic Modelling, Water Quality Modelling and Habitat Assessment for Sustainable Water Management: A Case Study of the Anyang-Cheon Stream, Korea

Recent ecological stream restoration projects have focused on expanding the water-friendly space of streams, promoting the health of aquatic ecosystems, and restoring various habitats, which raise the need for relevant research. Applying integrated environmental analysis, this study quantifies the change in hydraulic characteristics before and after the restoration projects through physical habitat simulation and links the results of physical impacts to estimate benefits of increase in water quality and aquatic ecosystem health due to the implementation of the project. For this, the study area is a 3.3 km long reach of the Anyang-cheon Stream, Korea. Field monitoring revealed that five fish species are dominant and sub-dominant, and account for 76% of the total fish community. To assess the change of before and after ecological stream restoration project, the River2D and Coastal Modelling System (CMS)-Flow 2D models were used for hydraulic and water quality simulations, respectively. For the habitat simulation, the HSI (Habitat Suitability Index) model was used. In addition, the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) was used to calculate changes in water quality index and to examine changes in habitat areas with an integrated quantitative index, the methodology of Zingraff-Hamed et al. was adopted. It was found that the ecological stream restoration project significantly increased for the eco-friendly area. In addition, the changes in water quality and habitat suitability grades before the ecological river restoration project were improved to two stages and one stage, respectively. This study applied the integrated analytical framework as a policy/project assessment tool and the results of this study will be useful for the integrated water management policy.
Determinants and long‐term costs of early reproduction in males of a long‐lived polygynous mammal

Abstract In long‐lived polygynous species, male reproductive success is often monopolized by a few mature dominant individuals. Young males are generally too small to be dominant and may employ alternative tactics; however, little is known about the determinants of reproductive success for young males. Understanding the causes and consequences of variability in early reproductive success may be crucial to assess the strength of sexual selection and possible long‐term trade‐offs among life‐history traits. Selective pressures driven by fluctuating environmental conditions may depend on age class. We evaluated the determinants of reproduction in male bighorn sheep (Ovis canadensis) aged 2–4 years using 30 years of individual‐level data. These young males cannot defend estrous ewes and use alternative mating tactics. We also investigated how the age of first detected reproduction was correlated to lifetime reproductive success and longevity. We found that reproductive success of males aged 3 years was positively correlated to body mass, to the proportion of males aged 2–4 years in the competitor pool, and to the number of females available per adult male. These results suggest that reproductive success depends on both competitive ability and population age–sex structure. None of these variables, however, had significant effects on the reproductive success of males aged 2 or 4 years. Known reproduction before the age of five increased lifetime reproductive success but decreased longevity, suggesting a long‐term survival cost of early reproduction. Our analyses reveal that both individual‐level phenotypic and population‐level demographic variables influence reproductive success by young males and provide a rare assessment of fitness trade‐offs in wild polygynous males.
An Ecological Assessment of Critically Endangered Chinese Pangolin Manis pentadactyla (Mammalia: Pholidota: Manidae) in the Midhills Region of Nepal

The Chinese Pangolin (Manis pentadactyla) is a “Critically Endangered” insectivorous mammal. There is a lack of information on the ecology, distribution and behavior of this species in Nepal, even though community forests in the Midhills Region of Nepal are considered to be prime habitats for the species. We conducted an ecological assessment of the habitat use of this species in nine community forests covering an area of 170.69 ha in Balthali village in Kavrepalanchok district, Nepal. We divided each forest into 50 × 50 m grids and searched for Chinese Pangolin burrows along 50 m transects in each grid. We categorized burrows into two types, new and old burrows, and recorded 10 environmental variables for each burrow. We found a total of 542 burrows, including 323 old burrows and 219 new burrows. The average width and height of a burrow opening was 21.66 ± 3.94 cm (n = 542) and 22.42 ± 5.02 cm (n = 542). The total density of burrows in the study area was 3.1 ha−1, with new burrows density of 1.2 ha−1 and old burrows density of 1.8 ha−1. We found most burrows in sites with an elevation range of 1400 - 1500 m above sea level, gentle slopes, brown colored soil, high density of tree crown cover and undergrowth vegetation, southern exposure, within 150 m from a water source and less than 200 m from a human settlement. Our study has generated baseline data on the habitat use of Chinese Pangolin, which we hope will help in designing site-specific action plans for Chinese Pangolin conservation in Kavrepalanchok district, Nepal.
Lost in the Transition: The Cost of College-Readiness English Standards Misalignment for Students Initially Classified as English Learners

ABSTRACT Using linked, individual-level data from a large metropolitan K-12 district and a large urban community college district in California, we examine whether indicators of college-readiness for graduating high school students who were initially classified as English Learners (ELs) are honored in community college course placement. In particular, we explore (1) whether there is misalignment in course assignment levels among former EL students between the K-12 and community college sector based on high school readiness metrics; and (2) if misalignment exists, we investigate its extent among various levels and identities of EL students. We employ an integrated capitals and funds of knowledge framework to emphasize students’ assets in the form of resources, knowledge, and skills while also acknowledging the role of education systems in reproducing social inequities. We find that along with students who speak Spanish at home, Latina/o, and Black students, former ELs who met college-readiness standards experienced the highest levels of inter-sector English misalignment (over 75%). Our results show a negative association between experiencing inter-sector misalignment and college credit accumulation. After controlling for course placement, background, and academic characteristics our analysis suggests that despite facing higher levels of inter-sector misalignment relative to other students, former ELs manage to accumulate five to six more transferable degree units than their monolingual English-speaking peers. The findings suggest a need for even greater inter-sector communication and accountability between legislators, K-12, and postsecondary leaders to ensure that state-level college-readiness standards are properly defined and consistently used in the transition from high school to college.
Dynamic Forecasting of Government Foreign Debt: Case of Indonesia

This study aims to forecast the value of the Indonesian government foreign debt in 2020-2024. The secondary data of time series during the period of 2010-2019 on Indonesian government foreign debt are used as the basis of forecasting for the next five years by using ARIMA (Autogressive Integrated Moving Average). The results show that the selected ARIMA models for forecasting are ARIMA (3,1,3) after the unit root test is carried out and 16 ARIMA models are tested. The value of government foreign debt is predicted to keep increasing from 2020 to 2024 amounted to USD 253.01. Then, compared to government debt in January 2010, within 11 years, government foreignÂ debt is predicted to rise by 169.6%.
Financial Evaluation by the Combined AHP-PROMETHEE Method: A Case Study of Integrated Logistics Service Providers in Thailand

In relation to core competence, cost reduction and improvement of customer satisfaction, an outsourcing has noticeably become a crucial strategy to cope with those of numerous firms. Logistics services (such as management of inventory and transport) have been emerged as one of the outsourcing activities, which a logistics service provider performs its logistics capability to fulfill operations of any firm tied up with the complex networks of supply chain. In this case, the financial performance of integrated logistics service providers located in Thailand were compared through the notion of multi-criteria decision making (MCDM). Therefore, the combined AHP-PROMETHEE method was proposed in this study. AHP was utilized to determine weights of four criteria and 15 sub-criteria based directly on financial ratios, while PROMETHEE was employed to evaluate and rank four pre-determined alternatives of integrated logistics service provider from the best to worst one on financial ability. As a consequence, an outcome shows that III is viewed as the best organization among others for manipulating on the whole finance efficiently. Ultimately, this is a benchmark for other firms to improve their financial performance, and investors can manipulate this method as a tool to carefully invest in the stock market. Keywords: AHP, Financial Ratio, Logistics Service Provider, MCDM, PROMETHEE
Paint detection in shortwave and midwave hyperspectral using one dimensional CNN and guided grad-CAM band selection

Short wave infrared (SWIR) is the reflected radiance in the 1-2.5 μm range. Mid wave infrared (MWIR) is the radiated radiance in the 3-5 μm range. This paper proposes a paint detection method using two infrared bands with different characteristics. Object detection is one of the issues in hyperspectral image (HSI). We use one dimensional convolution neural network (1D-CNN) and guided gradient-weighted class activation mapping (Guided Grad-CAM) for band selection. We make a 1D-CNN architecture and select bands using Guided Grad- CAM from well-trained 1D-CNN. Finally, paint is detected using selected bands. We use datasets included short wave infrared band (SWIR) and mid wave infrared band (MWIR).
Comparison of K-means and K-means++ for image compression with thermographic images

Compression algorithms have been implemented for k-means and k-means++ clustering and applied to thermographic images. The overall algorithm has four stages and are the same for the two algorithms except for the initialization of the centroids. The compression ratio and quality are primarily dependent on the number of clusters used for the algorithm. A MATLAB GUI was developed to run the algorithms and a comparison has been performed with subjective evaluations and objective RMS error, peak SNR and compression ratio metrics. The average compression ratio was 1.3 and 1.6 for the k-means and k-means++ clustering respectively. The k-means++ clustering provides subjectively better visual results than the standard k-means clustering.
Production of amygdalin by means of callus culture in some Prunus species

Amygdalin is a glycoside which commonly found in the seeds of stone fruits. This active ingredient has a great importance in drug industry. Amygdalin is commonly obtained from the seeds of three different Prunus species (almond, cherry laurel and apricot) by producing in vitro callus cultures. In this study, analyses of amygdalin was performed with HPLC from the explants, calluses and kernels of these three species. According to the results obtained, the maximum amygdalin was noted from the whole kernel of the apricot fruits as 5888.45 mg per 100 gwhereas the maximum amygdalin content of cotyledons was 213.47 mg per 100 g which was measured from the almond explants. Amygdalin content of the Prunus calluses were then noted as 1376.13 mg, 140.74 mg and 74.08 mg in 100 g at cherry laurel, apricot and almond, respectively. Present results suggested that the callus cultures of Prunus species can be used in order to obtain amygdalin. Key word: Prunus, Callus, Amygdalin, Secondary Metabolite, HPLC.
Thinking with complexity in evaluation: A case study review

Adopting complexity thinking in the design, implementation and evaluation of health and social development programmes is of increasing interest. Understanding institutional contexts in which these programmes are located directly influences shaping and eventual uptake of evaluations and relevant findings. A nuanced appreciation of the relationship between complexity, institutional arrangements and evaluation theory and practice provides an opportunity to optimise both programme design and eventual success. However, the application of complexity and systems thinking within programme design and evaluation is variously understood. Some understand complexity as the multiple constituent aspects within a system, while others take a more sociological approach, understanding interactions between beliefs, ideas and systems as mechanisms of change. This article adopts an exploratory approach to examine complexity thinking in the relational, recursive interactions between context and project design, implementation and evaluation. In doing so, common terms will be used to demonstrate the nature of shared aspects of complexity across apparently different projects.
Q-Learning based Routing Protocol to Enhance Network Lifetime in WSNs

In resource constraint Wireless Sensor Networks (WSNs), enhancement of network lifetime has been one of the significantly challenging issues for the researchers. Researchers have been exploiting machine learning techniques, in particular reinforcement learning, to achieve efficient solutions in the domain of WSN. The objective of this paper is to apply Q-learning, a reinforcement learning technique, to enhance the lifetime of the network, by developing distributed routing protocols. Q-learning is an attractive choice for routing due to its low computational requirements and additional memory demands. To facilitate an agent running at each node to take an optimal action, the approach considers node’s residual energy, hop length to sink and transmission power. The parameters, residual energy and hop length, are used to calculate the Q-value, which in turn is used to decide the optimal next-hop for routing. The proposed protocols’ performance is evaluated through NS3 simulations, and compared with AODV protocol in terms of network lifetime, throughput and end-to-end delay.
Performance evaluation for an hourglass‐shaped impedance‐network‐based high step‐up converter in a photovoltaic system using PSIM© simulation

In this paper, the control design and the performance evaluation of a novel high step‐up converter with an hourglass‐shaped impedance network (HIN) are performed when used as an interface between a photovoltaic (PV) source and a load in a PV system. For optimum energy extraction from the PV source, the PV voltage controller design and optimization to track the maximum power point of the PV system is addressed. The converter offers the possibility of an optimum regulation of the PV voltage with voltage mode control using a simple Type‐III compensation network resulting in a low overshoot, a relatively short settling time, and negligible energy loss after a change of input reference due to the maximum power point tracking (MPPT) or to irradiance change. To evaluate the performance of the HIN converter when used in a PV system, PSIM©software is used to perform numerical simulations using the switched model under different conditions.
Hacking Ion 2018 – knowledge management to develop entrepreneurship in the field of ionizing radiation metrology

Hacking Ion 2018 was the first scientific marathon (Hackathon) in the area of Ionizing Radiation Metrology (IRM) in Brazil and Latin America. The event took place during the 2018 IRM Congress, on the campus of the Institute of Radiation Protection and Dosimetry (IRD), and was aimed at stimulating entrepreneurship among students of the IRD Graduate Program, based on generating technologies in order to present solutions for the development of research in the area of IRM. The event was attended by 16 students, divided into 4 teams, with a time limit of 48 hours to think and develop solutions based on the proposed themes. At the end of the third day, they presented their projects to a judging panel and to the participants in the Congress. Throughout the process, the students were guided by a representative of the Brazilian Service of Support to Micro and Small Enterprises (SEBRAE), who initially offered a lecture and a startup preparation workshop. The winning project was the School in Glasses team, which developed a distance learning platform that uses virtual and augmented reality in the area of radioprotection. It is understood that this event serves as a stimulus for students to develop ideas in their respective areas of research, so that new work tools can arise in the aid of Knowledge Management in IRM.
Human Capital in Court

Human capital theory suggests that work experience acquired through on-the-job-training primes people to be more successful. Empirical validations of this hypothesis are numerous, but limited evidence of the relevance of human capital for courtroom advocacy exists. We examine whether the outcomes obtained by experienced attorneys are significantly better than the outcomes they would have obtained as novices. Adopting a strategy for credible causal inference that could be applied to almost any peak court, the analysis shows that attorneys with experience, relative to first timers, are significantly and consistently more likely to win their cases and capture the votes of judges.
Historical Corpora Correlation based on RNN and DCNN

Correcting historical corpora in digital version is a crucial task for the historical research, however, scan quality, book layout, visual character similarity can affect the quality of the recognizing. OCR is at the forefront of digitization projects for cultural heritage preservation. The main task is to identify characters from their visual form into their textual representation. In this paper, we propose a model combining recurrent neutral network(RNN) and deep convolutional network(DCNN) to correct OCR transcription errors. The experiment on a historical book corpus in German language shows that the model is very robust in capturing diverse OCR transcription errors greatly.
Road network detection based on improved FLICM-MRF method using high resolution SAR images

The automatic detection of road network from satellite and aerial images is highly significant in many actual applications, for instance, urban traffic measurement, military emergency response, and vehicle target tracking. Compared with other high-resolution satellite remote sensing images, high-resolution synthetic aperture radar (SAR) has become a popular research perspective for road detection owing to its insensitivity to the atmosphere and sun-illumination. However, the method of road network detection is still lagging due to the strong multiplicative speckle noise and complex background interference, causing the loss and break in the road segment extraction results. Aiming to solve this problem, a three-step road network detection framework is proposed. In the first step, the road segment candidates are extracted by the Fuzzy Local Information C-Means (FLICM) algorithm based on the gray-level co-occurrence matrix(GLCM) with Markov Random Fields (MRF), and it contains an adaptive parameter selection procedure which is presented for adjusting joint clustering parameters. In order to reduce false segments, we perform the local processing which combines the morphological operation, linearity index, and local Hough transform in the second step. Finally, as for the global road segment connection, we propose an improved region growing algorithm which fully considering the rationality of road elements to gain the road network. Compared with the traditional region growing algorithm, the proposed method can effectively promote the improvement of the integrity of the road network detection. Moreover, the performance of the proposed method is evaluated by comparing the results with the ground truth road map and the evaluation index including the completeness, correctness, and quality factor. In experiments, the algorithm has been verified with the SAR images from the different resolutions of the GF-3 satellite SAR image. The results of the various real images demonstrate that the proposed algorithm has improved considerably the adaptability and efficiency of road detection compared with other methods.
Mathematical modelling of biology processes based on the table of prime links in the solid torus up to 4 crossings

The motivation to study links in lens spaces can be justified in recent applications to theoretical physics and biology. In this paper, we give a short outline of practical significance and implementation proposals of such links, the study of which begins with the study of links in the solid torus, since a punctured disk diagram of a link in the lens space can be considered as a punctured disk diagram in the solid torus provided with the additional slide move. However, links in the solid torus find their applications themselves as well. In this paper, we propose a method to represent knotted proteins as links in the solid torus. Such a method is based on the existence of correspondence between knotoids and knots in the solid torus using a double branched cover. To this end, the table of links in solid torus is necessary. Therefore, we classify all prime links in the solid torus up to 4 crossings. One of possible future applications of the constructed table is an analysis of the database LinkProt that collects information about protein chains and complexes that form links. Also, our table can be used to construct table of prime links in lens spaces.
An application on fish bones by chemical modification of histidine as amino acid

In this study, fish bones as a waste in fish processing was investigated whether they could be used as multi-functional materials by chemical modification. Histidine was used and modified on the surface of bone particle by esterification method. The reaction was carried out in water. The results showed that the surface modification of bone particles was performed successfully. Histidine bonded on the surface of bone was calculated as 110.83 µmol/g. The point of zero charge (PZC) of bone apatite (H) and modified bone (HA 4 ) was investigated and determined as 7.25 and 6.98, respectively. SEM-EDX spectrums showed that nitrogen element of histidine on the surface of HA 4 could be observed in EDS spectrum clearly. According to EDS spectrum analysis, nitrogen amount of HA 4 which was formed to the one of histidine composition was detected as 16.2 %. , nitrogen amount of H and HA 5 was detected as 8.037% and 8.565 %, respectively.