Miracle-dz/UniFAR-FTUs huggingface dataset:
Decadal Assessment of Sperm Whale Site-Specific Abundance Trends in the Northern Gulf of Mexico Using Passive Acoustic Data

Passive acoustic monitoring has been successfully used to study deep-diving marine mammal populations. To assess regional population trends of sperm whales in the northern Gulf of Mexico (GoM), including impacts of the Deepwater Horizon platform oil spill in 2010, the Littoral Acoustic Demonstration Center-Gulf Ecological Monitoring and Modeling (LADC-GEMM) consortium collected broadband acoustic data in the Mississippi Valley/Canyon area between 2007 and 2017 using bottom-anchored moorings. These data allow the inference of short-term and long-term variations in site-specific abundances of sperm whales derived from their acoustic activity. A comparison is made between the abundances of sperm whales at specific sites in different years before and after the oil spill by estimating the regional abundance density. The results show that sperm whales were present in the region throughout the entire monitoring period. A habitat preference shift was observed for sperm whales after the 2010 oil spill with higher activities at sites farther away from the spill site. A comparison of the 2007 and 2015 results shows that the overall regional abundance of sperm whales did not recover to pre-spill levels. The results indicate that long-term spatially distributed acoustic monitoring is critical in characterizing sperm whale population changes and in understanding how environmental stressors impact regional abundances and the habitat use of sperm whales.
Determinants Effectiveness Information Technology Governance in Higher Education Institution (HEI) using partial least squares structural equation modeling approach (PLS-SEM)

Information technology supports the achievement of business organization objectives. The Higher Education institution is a business organization engaged in the field of education. Effective IT governance will ensure alignment between IT and business goals. Organizations with ineffective IT governance will suffer due to poor performance of IT resources such as inaccurate information quality, inefficient operating costs, runaway IT project and even the demise of its IT department. This study seeks to examine empirically the individual IT governance mechanisms that influence the overall effectiveness of IT governance. Furthermore, this study examines the relationship of effective IT governance and IT Innovation within the Higher education organizations. The sampling technique to be carried out in this study is a multi-stage purposeful random sampling. In sequence, researchers will combine surveys through online. The quantitative data were analyzed by the smallest partial quadratic structural equation method (PLS-SEM) using Smart PLS 3.0. The results obtained from this dataset show a positive significant relationship between effective IT governance and the following mechanisms: IT Steering Committee, Involvement of Senior management in IT, and Organizational Communication System. Also a positive relationship between ITG Effectiveness within IT Innovation. Organizational Communication System and IT Innovation have a positive significant relationship, and negative relationship with insignificant for Organizational Performance Measurement System.
Deep Learning for Daily Precipitation and Temperature Downscaling

Downscaling is a critical step to bridge the gap between large‐scale climate information and local‐scale impact assessment. This study presents a novel deep learning approach: Super Resolution Deep Residual Network (SRDRN) for downscaling daily precipitation and temperature. This approach was constructed based on an advanced deep convolutional neural network with residual blocks and batch normalizations. The data augmentation technique was utilized to address overfitting that is due to highly imbalanced precipitation and nonprecipitation days and sparse precipitation extremes. Synthetic experiments were designed to downscale daily maximum/minimum temperature and precipitation data from coarse resolutions (25, 50, and 100 km) to a high resolution (4 km). The results showed that, during the validation period, the SRDRN approach not only captured the spatial and temporal patterns remarkably well, but also reproduced both precipitation and temperature extremes in different locations and time at the local scale. Through transfer learning, the trained SRDRN model in one region was directly applied to downscale precipitation in another region with a different environment, and the results showed notable improvement compared to classic statistical downscaling methods. The outstanding performance of the SRDRN approach stemmed from its ability to fully extract spatial features without suffering from degradation and overfitting issues due to the incorporations of residual blocks, batch normalizations, and data augmentations. The SRDRN approach is thus a powerful tool for downscaling daily precipitation and temperature and can potentially be leveraged to downscale any hydrologic, climate, and earth system data.
Chemical Variability of Salvia eremophila Boiss. (Case Study: Yazd Province, Iran)

Salvia eremophila Boiss. is an endemic plant from Iran. Plant metabolites are directly affected by some environmental factors. In following, secondary metabolites and chemical compounds might be varied that this variation can lead to changes the pharmacological efficacies. To investigate chemical variation of the species in different natural habitats, the essential oils were extracted by hydro-distillation method using Clevenger apparatus. Comparative outcomes revealed considerable variations in the obtained oils and constitutions. The essential oil yield varied between 0.69 – 0.81% during full flowering stages. The essential oil analyses identified 14 compounds (86.7 – 94.1% of the total oil) among which α-pinene (48.7 – 52.7%) was the highest component in all studied populations. The other main compositions were borneol (11.5 – 14.7%), isobornyl acetate (9.1 - 10.8%), and trans-Caryophyllene (6.9 – 8.2%). Based on the present research it could be found that chemical variation of S. eremophila in the studied areas is considerable. Ghavam Abad was the best one in quality and quantity of the chemical compounds.
Myanmar Continuous Speech Recognition System Using Convolutional Neural Network

: Translating the human speech signal into the text words is also known as Automatic Speech Recognition System (ASR) that is still many challenges in the processes of continuous speech recognition. Recognition System for Continuous speech develops with the four processes: segmentation, extraction the feature, classification and then recognition. Nowadays, because of the various changes of weather condition, the weather news becomes very important part for everybody. Mostly, the deaf people can’t hear weather news when the weather news is broadcast by using radio and television channel but the deaf people also need to know about that news report. This system designed to classify and recognize the weather news words as the Myanmar texts on the sounds of Myanmar weather news reporting. In this system, two types of input features are used based on Mel Frequency Cepstral Coefficient (MFCC) feature extraction method such MFCC features and MFCC features images. Then these two types of features are trained to build the acoustic model and are classified these features using the Convolutional Neural Network (CNN) classifiers. As the experimental result, The Word Error Rate (WER) of this entire system is 18.75% on the MFCC features and 11.2% on the MFCC features images.
Investor attention, uncertainty and travel & leisure stock returns amid the COVID-19 pandemic

ABSTRACT This study examines the impact of investor attention, and economic policy uncertainty on travel & leisure stocks returns amid the COVID-19 pandemic. We use Google search volume (GSV) and economic policy uncertainty (EPU) as a proxy for investor attention and uncertainty. Our findings indicate greater sensitivity of travel & leisure stock returns to investor attention and economic policy uncertainty amid the COVID-19 crisis period.
Performance Analysis of a Low Power High Speed Hybrid Full Adder Circuit and Full Subtractor Circuit

In this paper, a hybrid 1-bit adder and 1-bit Subtractor designs are implemented. The hybrid adder circuit is constructed using CMOS (complementary metal oxide semiconductor) logic along with pass transistor logic. The design can be extended 16 and 32 bits lately. The proposed full adder circuit is compared with the existing conventional adders in terms of power, delay and area in order to obtain a better circuit that serves the present day needs of people. The existing 1-bit hybrid adder uses EXNOR logic combined with the transmission gate logic. For a supply voltage of 1.8V the average power consumption (4.1563 µW) which is extremely low with moderately low delay (224 ps) resulting because of the deliberate incorporation of very weak CMOS inverters coupled with strong transmission gates. At 1.2V supply the power and delay were recorded to be 1.17664 µW and 91.3 ps. The design was implemented using 1-bit which can also be extended into a 32-bit design later. The designed implementation offers a better performance in terms of power and speed compared to the existing full adder design styles. The circuits were implemented in DSCH2 and Microwind tools respectively. The parameters such as power, delay, layout area and speed of the proposed circuit design is compared with pass transistor logic, adiabatic logic, transmission gate adder and so on. The circuit is also designed with a decrease in transistors in order to get the better results. Full Subtractor, a combinational digital circuit which performs 1-bit subtraction with borrow in is designed as a part of this project. The main aim behind this part of the project is to design a 1-bit full Subtractor using CMOS technology with reduced number of transistors and hence the efficiency in terms of area, power and speed have been calculated is designed using 8,10,15and 16 transistors. The parameters were calculated in each case and the results have been tabulated.
Bilinguals on the garden-path: Individual differences in syntactic ambiguity resolution

Abstract Syntactic parsing plays a central role in the interpretation of sentences, but it is unclear to what extent non-native speakers can deploy native-like grammatical knowledge during online comprehension. The current eye-tracking study investigated how Chinese–English bilinguals and native English speakers respond to syntactic category and subcategorization information while reading sentences with object-subject ambiguities. We also obtained measures of English language experience, working memory capacity, and executive function to determine how these cognitive variables influence online parsing. During reading, monolinguals and bilinguals showed similar garden-path effects related to syntactic reanalysis, but native English speakers responded more robustly to verb subcategorization cues. Readers with greater language experience and executive function showed increased sensitivity to verb subcategorization cues, but parsing was not influenced by working memory capacity. These results are consistent with exposure-based accounts of bilingual sentence processing, and they support a link between syntactic processing and domain-general cognitive control.
Medical Image Analysis based on Global Contrast Enhancement using Bilateral Filtering

: In the field of medical imaging the scanning technology is advancing day by day. With the help of various technologies like X-ray imaging, Computed Tomography and Magnetic Resonance Imaging it becomes very easy to diagnose the patient diseases. Now there are various limitations which can degrade the performance of the generated images from the hardware scanning machines. So to detect the various types of diseases the output digital images should be enhanced and processed fairly well. The main reason of not detecting the depth of the disease is the generation of low contrast medical images. Also in various internal surgeries of the human body the live camera feed is used to get the insight of various interested human parts and for that the images received should be processed and enhanced immediately by the used algorithms. The sizes of the detected objects and their shape and their periphery should be properly visible so that surgery could be successful. In the present research the global contrast enhancement of the medical images is done with the help of bilateral filtering. Further medical images are enhanced to get good and refined edges and for achieving it also various types of filters are used to get the refined medical images. The output of the proposed algorithm is compared with other medical image enhancement techniques. Various objective performance evaluation parameters like mean square error, peak signal to noise ratio are used for providing worthiness of proposed algorithm for contras enhancement of medical images.
Babesiosis in a -3-Month-old Nigerian Indigenous Male Puppy

Babesiosis is a protozoan disease caused by Babesia spp, which is an intra-erythrocytic parasite of domestic and wild animals. The parasite is mainly transmitted by infected ticks through bite and it is characterized by fever, paleness and icteric mucous membranes and emaciation. This paper reports case of babesiosis in a 3-month-old Nigerian indigenous male puppy at Veterinary Teaching Hospital, Ahmadu Bello University, Zaria. The relevant history, clinical signs and laboratory evaluations were recorded. The effects on some hematological parameters were studied and recorded. The dog was successfully transfused with 226 ml of blood and then treated with a single dose of 4% Diminazene aceturate at the dose rate of 4 mg/kg intramuscularly (I.M). Thereafter, the patient was monitored until fully recovered.
Scientific intelligence, nuclear assistance, and bargaining

Members of the non-proliferation regime give technical assistance to countries contemplating nuclear weapons. This is puzzling: it facilitates the behavior donors wish to stop, and other forms of concessions do not have this drawback. Why do it? I develop a model of uncertainty, bargaining, and nuclear proliferation. In it, assistance hastens acquisition time but also generates a signal about the recipient’s domestic nuclear proficiency. This allows donors to better calibrate other concessions to the recipient. In equilibrium, donors sometimes find the information worth sacrificing bargaining leverage for. However, despite providing information, assistance can cause proliferation if donors believe that the recipient is competent but observe a misleading signal indicating incompetence. This paper works toward understanding how scientific intelligence affects international negotiations, an underexplored subject matter for political scientists.
Urban–Rural Dichotomy in Planning: Review of Legal Framework in Four States of India

Current urbanisation trends in India show a quantum jump in number of ‘census towns’, which are not statutorily declared as urban areas, but have acquired all characteristics of urban settlements. Sizeable number of such census towns are not located near any Class 1 city. Lack of proper and timely planning has led to unplanned growth of these settlements. This article is based on a review of planning legislations, institutional framework and planning process of four states in India. The present article analyses the scope and limitations of the planning process adopted in the rapidly urbanising rural areas of these states. The findings reveal that states are still following a conventional approach to planning that treats ‘urban’ and ‘rural’ as separate categories and highlights the need for adopting an integrated territorial approach to planning of settlements.
Distribution of eight heavy metals in the inner shelf sediments of East China Sea: Risk assessments and sources analysis

ABSTRACT Although numerous studies on heavy metals (HMs) in sediments have been carried out in the East China Sea (ECS), the knowledge on the recent pollution levels of HMs in coastal region remains not well understood due to the rapid developments of urbanization in eastern China. In this study, 23 surface samples and 4 core samples are collected in the inner shelf of the ECS. The average dry-weight concentrations follow the descending order of Zn, Cr, Ni, Pb, Cu, As, Cd, and Hg (103.6 ± 26.0, 42.8 ± 12.4, 37.0 ± 9.1, 34.7 ± 11.1, 19.5 ± 10.3, 15.7 ± 11.6, 0.056 ± 0.017, and 0.041 ± 0.017 μg g−1, respectively). HMs concentrations share a similar spatial distribution pattern of TOC content with a decreasing trend from coastline to outer sea. Additionally, HMs concentrations exhibit a decreasing trend from top to bottom sediments, especially for Hg at the open sites due to the wet and dry deposition of atmospheric Hg besides the riverine inputs. The potential ecological risk indices (PERI) values in coastal sediments were about 2–4 times higher than those in open sea. Although the Hg and Cd concentrations were lower by 2–3 orders of magnitude than those of other six metals, the PERI values of Hg (65.5) and Cd (52.1) were 3–40 times higher than those of others. The hierarchical cluster result is consistent with the PCA result, suggesting that Hg, Cd, and As have similar sources and probably mainly originated from anthropogenic emissions.
Pricing Strategy for Residential Water in Drought Years. Application to the City of Tianjin, China

In drought years, most residents fail to improve water use efficiency due to residential water supply normally being prioritized in many regions, which makes other low-priority industrial water users suffer more from water shortage. This paper proposes a Pricing Strategy for Residential Water (PSRW), a water tariff that changes on annual time scale, based on the scarcity value of water resources, aiming to promote residential water conservation and reallocate water resources across the residential and industrial sectors during droughts. An optimization model to maximize the total benefit of residents and industrial sectors is introduced based on marginal benefit and price elasticity. The water shortage of industrial sectors is used to reflect the scarcity of water resources, and the lowest water supply standard for households and the maximum proportion of household water fee expenditure (HWFE) to household disposable income (HDI) are used to ensure the residents’ acceptability to price raising. It shows an “S-type” relationship between the optimal price raising coefficient and industrial water shortage, and two turning points are found in the curve, which are the starting and stopping points of price raising. The appearance of starting point depends on the non-negative net benefit, and the stopping point is affected by the factors that represent the residents’ acceptability to price raising. The application to Tianjin, a city in northern China with the rapid growth of population and economy but scarce water resources, shows PSRW is a potential means to improve water efficiency and optimize water resource allocation in water scarcity situations.
Artificial Heart Neural Networks – An Idea

Artificial Neural Networks Field (ANN Field) is an exciting field of research. ANN field took its inspiration from Human Brain. The heart and Brain are very important for the survival of Humans. Research Scientists published many articles by giving importance to Brain. But scientists have not yet explored much on the Heart which is another important part in addition to the Brain. The primary purpose of publishing this article is to show a path to ANN field Research Scientists by introducing the concept of “Heart” into Artificial Neural Networks. In this paper, we coined and defined “Artificial Heart Neuron,” which is the basic part of Artificial Heart Neural Networks Field (AHNN Field) in addition to Artificial Neuron. This work takes its inspiration from both Heart and Brain.
Stakeholder’s Risk Perceptions of Wild Pigs: Is There a Gender Difference?

Substantial literature indicates that genders differ in terms of risk perception and values regarding wildlife management. Lack of equal stakeholder representation is also documented, which can also impact the effectiveness of human-wildlife conflict resolution interventions and education and outreach efforts. This paper investigates gender differences in perceptions about risks and potential adverse impacts on production, health, environment, safety, and population management posed by wild pigs. A survey was used to collect data from a random sample of adult residents (N = 1221) in Louisiana. We analyzed responses from 226 female and 832 male producers. We observed differences in how these groups perceive production risk and health risk. No distinct differences were found on how the two genders perceive wild pig impact on natural resources and safety. No difference is reported on how the two genders consider the management of the wild pig population.
Comparison of active components in two processed products of Polygonum multiflorum

Objective To provide basis for choosing a proper processed method of Polygonum multiflorum.Methods To compare and analyze main active component changes in the processed products of P.multiflorum by being steamed without any adjuvants and with soya-bean milk of different concentrations.Results There was no marked difference for variously processed products in the main active components,anthraquinone and stilbene glucoside in P.multiflorum. Conclusion It is feasible to replace the steamed with soya-bean milk by the steamed without any adjuvants.
State estimation problem for the detection of valve closure in gas pipelines

The undesired and unexpected closure of valves in pipelines is the most frequent failure that causes interruptions in the transport of natural gas. This work aims at the detection of valve closures by solving a state estimation problem with the Particle Filter method. The gas flow problem in the duct is solved with a Weighted Average Flux – Total Variation Diminishing scheme, while state variables are estimated with simulated measurements of pressure, velocity and temperature at different points along the pipeline. Two versions of the particle filter method are implemented in this work for the solution of the state estimation problem, namely, the Sampling Importance Resampling (SIR) and the Auxiliary Sampling Importance Resampling (ASIR) algorithms. Accurate estimations were obtained with both algorithms for configurations involving pipelines with one or three valves. On the other hand, the SIR algorithm required a larger number of particles than the ASIR algorithm for the same solution accuracy.
Double strand break (DSB) repair pathways in plants and their application in genome engineering

In genome engineering, after targeted induction of double strand breaks (DSBs) researchers take advantage of the organisms’ own repair mechanisms to induce different kinds of sequence changes into the genome. Therefore, understanding of the underlying mechanisms is essential. This chapter will review in detail the two main pathways of DSB repair in plant cells, non-homologous end joining (NHEJ) and homologous recombination (HR) and sum up what we have learned over the last decades about them. We summarize the different models that have been proposed and set these into relation with the molecular outcomes of different classes of DSB repair. Moreover, we describe the factors that have been identified to be involved in these pathways. Applying this knowledge of DSB repair should help us to improve the efficiency of different types of genome engineering in plants.