Miracle-dz/UniFAR-FTUs huggingface dataset:
Global analysis of response and recovery of benthic biota to fishing

Towed bottom-fishing gears are thought to constitute one of the largest global anthropogenic sources of disturbance to the seabed and its biota. The current drive towards an ecosystem approach in fish- eries management requires a consideration of the im- plications of habitat deterioration and an understand- ing of the potential for restoration. We undertook a meta-analysis of 101 different fishing impact manipu- lations. The direct effects of different types of fishing gear were strongly habitat-specific. The most severe impact occurred in biogenic habitats in response to scallop-dredging. Analysis of the response of differ- ent feeding guilds to disturbance from fishing re- vealed that both deposit- and suspension-feeders were consistently vulnerable to scallop dredging across gravel, sand and mud habitats, while the re- sponse of these groups to beam-trawling was highly dependent upon habitat type. The biota of soft-sedi- ment habitats, in particular muddy sands, were sur- prisingly vulnerable, with predicted recovery times measured in years. Slow-growing large-biomass biota such as sponges and soft corals took much longer to recover (up to 8 yr) than biota with shorter life-spans such as polychaetes (<1 yr). The results give a possi- ble basis for predicting the outcome of the use of dif- ferent fishing gears in a variety of habitats with poten- tial utility in a management context.
Strategies adopted by Nairobi java house to gain competitive advantage

The hospitality industry has in the last couple of years seen a transformation and dramatic changes which are brought about by competition. The study looked and analyzed as study objective, the strategies the company has adopted to achieve competitive advantage over its rivals. On another objective, it ventured on the challenges the company encounters in application of the said strategies and how it counters the challenges. The design used was ideal for the research problem since it allowed for an expansive data collection and thorough analysis of the data collected. By using a case study, the researcher was able to probe, collect data and explain phenomenon more deeply and exhaustively. The study found out that the strategies that Nairobi Java House adopts to achieve competitive advantage include: differentiation; product development; product pricing; market development; market expansion; diversification; and cost leadership strategy. It also found out that to apply these strategies, the company goes through some challenges like prior strategic commitments that hamper company ability to compete, lack of staff training and growth, other competing restaurants opening up business close by, product inconsistency and supplier unreliability. The study made the conclusion that Nairobi Java House operates in a very competitive environment. However, the company has been able to compete and achieve competitive advantage from the strategies it employs. It concluded also that companies do not gain competitive advantage by employing one strategy but by using a number of them so as to compete with all the competitors. If the company is able to maintain the use of these strategies effectively, then it would keep its position as a market leader. The company has also been able to counter its challenges by using readily available resources. The study recommended that the company should focus on its expansion speed considering its level of popularity so as to maintain its competitive edge.
Supply of cellulosic biomass in Illinois and implications for the Conservation Reserve Program

We developed a mathematical programming model to estimate the supply of cellulosic biomass in Illinois at various biomass prices and examine the implications of biomass production for the maintenance costs of the Conservation Reserve Program (CRP). We find that Illinois has the potential to produce about 38.4–54.5 million dry metric tons (MT) of biomass in 2020 at a biomass price of $150/MT, depending on the production costs of cellulosic feedstocks, residue collection technology, and rates of yield increases of conventional crops. Corn stover will account for more than 65% of the total biomass production across biomass prices and the scenarios considered, while the roles of wheat straw and energy crops are quite limited. Given biomass prices of $50/MT‐$150/MT, many landowners would convert their expiring CRP lands to croplands. To maintain the size of the CRP during the 2007–2020 period at the 2007 levels in Illinois, total program maintenance costs would be $104.6–176.5 million at a biomass price of $50/MT, depending on biomass production conditions and crop yields on CRP lands. This would increase to $155.2–245.4 million at a biomass price of $150/MT.
3D On-chip Data Center Networks Using Circuit Switches and Packet Switches

The energy consumption of the data center becomes a great problem. One approach to reduce the energy consumption of the data center is to use on-chip data centers, which are integrated circuit chips that perform the tasks in a data center. On-chip data centers are constructed of cores and the network between cores. Because the tasks in the data center are performed by the cooperation between servers, the network between cores in the on-chip data center may have a large impact on the performance of the chip. In this paper, we investigate the network structures for the on-chip data centers. We focus on the 3Dnetwork using both circuit and packet switches, and compare the energy consumption and the delay of the candidate network structures. The results show that (1) the servers should connect to the packet switches in the same layer, (2) the packet switches should connect to the circuit switches in all layers, and (3) the layer including both of circuit switches and packet switches should be avoided to reduce the energy consumption and the delay. Keywords—network on chip; data center; energy consumption; delay; 3D on-chip network
Detection of the need for seedling stand tending using high-resolution remote sensing data

Seedling stands are problematic in airborne laser scanning (ALS) based stand level forest management inventories, as the stem density and species proportions are difficult to estimate accurately using only remotely sensed data. Thus the seedling stands must still be checked in the field, which results in an increase in costs. In this study we tested an approach where ALS data and aerial images are used to directly classify the seedling stands into two categories: those that involve tending within the next five years and those which involve no tending. Standard ALS-based height and density features, together with texture and spectral features calculated from aerial images, were used as inputs to two classifiers: logistic regression and the support vector machine (SVM). The classifiers were trained using 208 seedling plots whose tending need was estimated by a local forestry expert. The classification was validated on 68 separate seedling stands. In the training data, the logistic model’s kappa coefficient was 0.55 and overall accuracy (OA) 77%. The SVM did slightly better with a kappa = 0.71 and an OA = 86%. In the stand level validation data, the performance decreased for both the logistic model (kappa = 0.38, OA = 71%) and the SVM (kappa = 0.37, OA = 72%). Thus our approach cannot totally replace the field checks. However, in considering the stands where the logistic model predictions had high reliability, the number of misclassifications reduced drastically. The SVM however, was not as good at recognizing reliable cases.
The risk factors of type 2 diabetic patients attending Rajshahi Diabetes Association, Rajshahi, Bangladesh and its primary prevention.

Diabetes is a serious harmful disease. The purpose of this study is to find out the risk factors of Type 2 diabetic patients in Bangladesh. For this purpose, the data are collected from the diabetic patients of Rajshahi Diabetes Association, Bangladesh. To fulfill this objective, chi square test and logistic regression analysis have been used. It is found that diabetes affects more in the age 35 years and over which is 89.7% in which 68.3% have type 2 diabetes. Again, 79.3% of diabetic patients have type 2 diabetes in which females (43.7%) are more affected than males (35.7%). It has been found that age, controlling diabetic through exercise, controlling diabetic through taking medicine and living house of the respondents are significantly associated with the type 2 diabetes of diabetic patients. It is also identified from logistic model that respondent's age, occupation, controlling diabetic through dieting, controlling diabetic through exercise, controlling diabetic through taking medicine, time spending in walking, calorie intake according to diabetic food table and living house of the respondents have statistically significant effect on type 2 diabetes. Diabetes is classed as a metabolism disorder. It is a group of diseases characterized by high levels of blood glucose resulting from defects in insulin production, insulin action and both, and is associated with serious complications and premature death. Also, diabetes mellitus is a major public health care problem with increasing incidence and long term complications. It is a leading cause of illness and death across the world which is associated with continuing damage, dysfunction and failure of various organs including lungs(1). The most common form of diabetes is type 2 diabetes which occurs when the pancreas is usually producing enough insu- lin but for unknown reasons the body can't use the insulin effectively (this condition is called insulin resistance). Diabetes is an emerging issue in developing as well as developed countries of the world. It was estimated that the number of people with diabetes globally would increase from current 171 million to 366 by 2030(2). In developed countries like United States which is one of the most vul- nerable places in terms of number of diabetic patients in which diabetes was the seventh leading cause of death listed
Research on Image Acquisition and Recognition for Stored Grain Pests

Manual ways of recognizing stored grain pests which are trapped is very time-consuming. In this study, an image dataset of 9 species of pests was built up by finding the MSERs (Maximally Stable Extremal Regions), through a trap of stored grain pests combined with a real-time imaging device. On this basis, the localization and recognition of stored grain pests were achieved. The experimental results on 3600 images showed that by the combination of shape features and color features, the average F1 score was about 0.947 by selecting the appropriate parameters of SVM (Support Vector Machines) classifier. Keywordsstored grain pests; image dataset; MSERs; color features; shape features
Lg Attenuation in a Region with Both Continental and Oceanic Environments

Abstract The crustally-guided shear wave, Lg , is typically the strongest phase at regional distances. Lg phases are analyzed often for estimation of magnitudes of regional events. The variation of Lg in regions with both continental and oceanic environments has been rarely investigated. We investigate Lg attenuation in a plate-margin area around Korea and Japan that is encompassed by seas and oceans. The mean quality factor of Lg at 1 Hz ( Q 0 ) is 498. The geometrical-spreading exponent term is estimated as 0.75. These observations characterize the study region as a high attenuation region compared to typical intraplate continental regions. Low- Q regions are widely developed over the Japanese islands, with some spotted high- Q regions. Relatively high Q is observed in most regions of the Korean Peninsula except a southeastern part where a Cretaceous volcanic-sediment basin exists. The high- Q values are close to the typical Q value in continental crust. Significantly low Q of 100 or less is observed in most oceanic regions including the East Sea (Sea of Japan), the Pacific Ocean, and the South China Sea. The high attenuation of Lg in oceanic regions suggests possible underestimation of magnitudes of oceanic events. Thus, it appears that proper correction of Lg amplitude is highly desired for accurate estimation of magnitudes of regional oceanic events.
Managing Supply for Construction Project with Uncertain Starting Date

There is a growing interest in supply management systems ¬¬in today’s competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers’ control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this thesis, we address the supplier selection problem (SSP) in wood-base construction projects in the presence of project commencement uncertainties. The project could be delayed for any reason and thus materials required for the project may not be needed on the promised date, however, pursuing the supplier for new delivery date may not be easy and without risk. Accepting the delivery before the project commencement date will be again a costly option because of the high holding cost. In this thesis, we present two problem cases and present heuristic based solution approaches. In the first case we assume that price of the product increases with the delay. In the second case we assume that promised quantity at the agreed price reduces with the delay. The proposed approaches are tested on the randomly generated data set and compared with the optimal solutions. The problems considered in this research are novel and the proposed approaches deal with the important and common risks in construction industry in order to achieve a robust supply chain. The solution approaches presented in this thesis can be applied to different industries to improve the quality and efficiency of supplier-buyer collaborations.
EFFICIENCY OF SHARIA AND CONVENTIONAL BANKS: EVIDENCE FROM INDONESIA

This study aims to evaluate the performance of Indonesian banking sector, comparing the technical efficiency of sharia and conventional banks along with the determinants of its efficiency during the period 2002-2010. Data Envelopment Analysis is employed to estimate banks technical efficiency and Tobit-regression is used to reveal the determinants of the efficiency over the panel data of 116 banks, including 109 conventional banks and 7 sharia banks. The result shows that sharia banks outperformed conventional banks in one model when it takes into account small business finance (SBF) as one of the output components in the model. Sharia banks have higher average SBF portfolio than those of conventional banks’ portfolio. The result indicates the efforts of Indonesian sharia banks to obey one of the principles in Islamic banking, “the emphasis on Islamic principles of morality”. By observing all models, it is concluded that the size of the bank, capital adequacy and liquidity are of banks characteristic factors which are very important to increase banks’ efficiency.
Value Creation and Appropriation of Firms: Concepts, Theories and Methodology

The issue of corporate performance had been vigorously addressed in the literature using traditional accounting metrics. However, contemporary studies now focus on corporate sustainability in terms of value creation and how constituents of a firm are compensated for their efforts at generating the value. The current research challenge is therefore on how to appropriately define and measure firm value, bearing in mind several stakeholders that have diverse and often conflicting interests in a firm. This paper fills this gap by using stakeholder perspective to explain the concept of value creation and by providing theoretical framework and methodology for measuring the value created and appropriated by a firm. It is established that value creation can be measured using (1) the difference between output value and inputs value, (2) the sum of the economic rewards given to stakeholders and 3) the true cash flows generated by a firm. The paper concludes that since the traditional accounting metrics have some limitations and since investors do not value accounting earnings but cash that is truly generated from a firm’ operations, a quantity that denotes value to diverse stakeholders of a firm should be used to measure firm value.
Effect of acid leaching of bamboo and hardwood chips on kraft pulping and pulp bleaching

Acid leaching of chips prior to pulping is a proven method to reduce non-process elements in kraft pulping process. In this paper, acid leaching of bamboo and hardwood chips was carried out at pH 2 for 1h at 80 °C prior to kraft pulping. Calcium removal in acid leaching from wood chips was 52.6% while for bamboo was only 17.4%. Acid leaching also reduced potassium (K) from 1258 mg/kg to 495.7 mg/kg for bamboo and 928 mg/kg to 562.5 mg/kg for wood chips. The effects of acid leaching on pulping, pulp bleaching, and papermaking characteristics were also determined. Acid leaching of both kinds of chips prior to kraft cooking resulted in a significant increase in the rate of delignification. Acid leached chips showed higher screen pulp yield and lower rejects at any kappa number. There was no significant difference of papermaking properties between pulps obtained from acid leached and non-leached chips. Using same ClO 2 charge, acid leaching improved pulp brightness by 1% and 1.1% for hardwood and bamboo, respectively. Acid leaching improved pulp viscosity from 10.1 mP.s to 12.1 mP.s for hardwood. Bangladesh J. Sci. Ind. Res. 51(4) , 247-252, 2016
Photonic integrated circuits on SOI for optical fiber communication applications

Optical fiber communication networks require a large amount of optical manipulation tools for transmitting, routing and receiving optical data. Although integration of photonic circuits on high index contrast platforms such as Silicon-on-Insulator (SOI) is key to decreasing the cost, size and power consumption, it is not straightforward to achieve optical performance comparable to discrete state-of-the-art components. We will present the recent advancements in realizing high performance integrated components such as fiber-to-chip couplers and polarization rotators. These components are envisioned in optical transceivers and optical routers using wavelength demultiplexing and higher-order modulation formats.
Cholesky Decomposition for the Vasicek Interest Rate Model

This paper concerns the estimation of parameters in the ``Vasicek Interest Rate'' model under a Bayesian framework. These popular models are challenging to fit with Markov chain Monte Carlo (McMC) methods as the structure of the model leads to considerable autocorrelation in the chains. Accordingly, we demonstrate that a simple re-parameterisation using the Cholesky decomposition can greatly improves the performance of the McMC algorithm and hence lead to valid Bayesian inference on the Vasicek model.
Quality of Net Income vs. Total Comprehensive Income in the Context of IAS/IFRS Regulation

Research in accounting has thus far attempted to provide fair and useful financial performance measures for a wide range of users. Academics and professionals have also established income as the key performance measures in making economic decisions. The purpose of this study is to investigate the quality of total comprehensive income (TCI) relative to net income (NI), prepared in accordance with International Financial Reporting Standards (IAS/IFRS). Using a data set covering 2,273 firms from 22 countries in Europe, Asia and Australia between 2006 and 2010, we provided evidence that net income always dominates comprehensive income as a valuation metric. The findings indicated that NI is more value relevant than TCI in predicting the future operating cash flows and income. In addition, NI is more persistent and timely, and explains the actual operating cash flows more precise than TCI. Accruals linked to NI have also better quality than those related to TCI. However, we found that TCI is less smoothing and more conservative than NI. These results do not support the claim that income measured on a comprehensive basis is a better measure of firm performance than NI. These results raise the questions about the usefulness of mandating TCI in IAS/IFRS regulation. Our findings, therefore, should be of interest to IASB, as they provide evidence of fewer quality of the TCI. Perhaps it is time for the IASB to reconsider other comprehensive income components and focus on items included in other comprehensive income to improve the quality of the TCI metric. These results also provide evidence of net income as a primary decision-relevant metric.
Face expression recognition using AR-BURG model and neural network

Neural network classifying method is used in this work to perform facial expression recognition. The processed expressions were the six most pertinent facial expressions and the neutral one. This operation was implemented in three steps. First, a neural network, trained using Zernike moments, was applied to the set of the well known Yale and JAFFE database images to perform face detection. In the second step, Auto Regressive modeling (AR) using 2D-Burg filter was used for facial parameterization. At the last step, a neural network, trained on a set of the AR models, was applied to the rest of the images models to test method's performances.
A Stochastic Dominance Approach to Program Evaluation with an Application to Child Nutritional Status in Kenya

Existing program evaluation methods such as difference‐in‐difference estimators or propensity score matching are designed to examine the average impact of a program. By design they can only examine changes in a particular summary statistic of an outcome indicator, most commonly the mean or the median or a particular quantile. However, we are often interested not only in the mean impact of an intervention, or the average treatment effect, but also the differential impact on different sub-populations such as the rich and the poor, the well‐nourished and the malnourished, or some finer disaggregation of the welfare domain. In principle, one could examine the program impact on various sub-populations by applying existing program evaluation techniques on smaller and smaller sub-samples of the data. In practice, this approach faces three main problems. First, it is cumbersome both for carrying out the analysis and for interpreting the results. Second, one faces arbitrary choices of how to split the sample. And third, increasing the number of subgroups leads smaller sample sizes and wider confidence intervals in the regression estimates. To circumvent these problems this article suggests a novel approach to program evaluation which combines stochastic dominance with difference‐in‐difference methods.