Miracle-dz/UniFAR-FTUs huggingface dataset:
Entropy in the ‘entrepot’: Examining the challenges of relief supply chains during COVID-19 pandemic relief item distribution operation-2020 in Uganda

Background: Distribution and management of relief supplies during hard times is seen as one of the key roles among governments in developing economies. Management of relief supply chains during a pandemic could be an uphill task that calls for an investigation. The present study focuses on the relief aid distribution of food items and face-masks during the first COVID-19 lockdown in Uganda. It specifically examines the challenges faced by the relief supply chain. Methods: It was a case study of stakeholders involved in relief distribution and conducted through electronic and physical interviews. 20 electronic interviews were conducted through zoom and telephone calls while 20 physical interviews were conducted at the interviewees’ respective workplaces. Data were collected from January 2021 to March 2021. The method of data collection and analysis was qualitative. Data were thematically analyzed using Atlas ti. v7.57. Results: It was found that many challenges ranging from needs identification, procurement, warehousing, transportation, handling, beneficiary verification, and distribution inhibited the proper functioning of the relief items distribution supply chain. Other obstacles were the media and its increasing influence on supply activities. Also, politics coupled with the emergence of new actors and governance issues were identified as part of the study findings. Conclusions: The present study identified a number of challenges in relief aid distribution. Some of the challenges were internal to the relief supply chain, others were beyond the chain. The findings could inform leverage of a number of factors during relief item distribution in the next cycles.
Semantically-Driven Search Techniques for Learning Boolean Program Trees

Title: Semantically-Driven Search Techniques for Learning Boolean Program Trees Author: Nicholas Charles Miller Principal Advisor: Philip K. Chan, Ph.D. Genetic programming has been around for over 20 years, yet most implementations are still based on sub-tree crossover and node mutation, in which structural changes are made that manipulate the syntax of programs. However, it is not clear why manipulating program syntax should have any desirable effect on program behavior (or semantics). One sub-field of genetic programming which has gained recent interest is semantic genetic programming, in which programs are evolved by manipulating program semantics instead of program syntax. A semantic GP (SGP) implementation exists that operates on program semantics through composition of sub-programs, but has the drawback that the evolved programs are large and complex. This paper will propose two new algorithms, SGP+ and SDPS, that aim to search the semantic space of programs in a more effective manner than the existing SGP algorithm. Experimental results on “deceptive” Boolean problems show that programs created by the SGP+ and SDPS algorithms are 3.8 and 32.5 times smaller than SGP respectively, while still maintaining accuracy as good as, or better than, SGP. Additionally, a 17.6% improvement in program accuracy was observed for several high-arity Boolean problems.
Measuring Complex for Determination of Temperature Characteristics of Thermistors

The article describes in detail the testing and operation principle of an autonomous measuring complex based on the stm32 microcontroller, designed to study the temperature dependence of the electrical resistance of thermistors and determine their parameters: 1) the coefficients included in the Steinhart - Hart equation; 2) thermal time constant characterizing the thermal inertia of the thermistor; 3) temperature coefficient of resistance.
Condition of Agricultural Productivity of Gosaba C.D. Block, South24 Parganas, West Bengal, India after Severe Cyclone Aila

On 25 th May 2009 morning severe cyclone Aila hit the Bay of Bengal coast of The Indian Sundarban region with it tidal surges of up to 6.5 metres, affecting 11 coastal districts. This surge of water damaged and washed away over 1,743kms of embankments, removing the only protection available to many people along the coast. This tidal surge causes floods over the entire region which brought high salinity and pH. This flood increased salinity and pH condition of agricultural land and highly affect over crop production. Crop production has markedly reduced after this severe cyclone. Economic conditions of the people in this region also highly affected by this natural disaster. Hodges, marks the northern limit of the Sundarbans, running in a slightly zigzag pattern from Basirhat in the north-east to Kulpi along the Hugli in the west. Politically the Sundarbans in North- 24 Parganas falls within the six Blocks of Minakhan, Haroa, Sandeshkhali-I and II, Hasnabad and Hingalganj while in South 24 Parganas it extends over thirteen Blocks of Gosaba, Basanti, Canning-I, Canning-II, Joynagar-I, Joynagar-II, Kultuli, Patharpratima, Namkhana, Sagar, Kakdwip and Mathurapur-II. The entire Indian Sundarban covers an area of 9630 sq. km bounded between estuary of river Hugli in the East, Bay of Bengal in the South, Ichhamati-Raimangal in the East and imaginary Dumpier and Hodges line in the North.
Contemporary seismicity in the eastern Snake River Plain, Idaho based on microearthquake monitoring

Microearthquake monitoring by a permanent network operated since 1971 and two recent temporary surveys performed by the Idaho National Engineering Laboratory suggest that infrequent, small-magnitude earthquakes are characteristic of eastern Snake River Plain (ESRP) seismicity. Although a total of only 19 earthquakes have been observed to date, and not all have well-constrained focal depths, their relatively shallow occurrence at depths of 8 km is consistent with the hypothesis that elevated crustal temperatures in the ESRP confine the brittle portion of the crust, and hence seismogenesis, to the upper 6 to 10 km. A composite focal mechanism of two microearthquakes located near the axis of the ESRP indicates normal faulting with a minor component of strike-slip motion. The northeast-southwest-trending T-axis indicated by this composite mechanism is consistent with the direction of extension indicated by Holocene volcanic rift zones within the ESRP and normal faults in the adjacent Basin and Range province to the northwest. Based on this low level of small-magnitude seismicity, deviatoric stresses appear to be small in the ESRP.
Modelling and Forecasting Claim Payments of Tanzania National Health Insurance Fund

The expenses of medical services are increasing across the globe. As a result, pressure is placed on government and insurance companies’ budgets. The amounts of money collected are not enough to cover the claim payments. Therefore, it threatens the sustainability of the health insurance companies due to the mismatch of income and expenditures. This study aimed to model and forecast claim payments for the national health insurance fund (NHIF) in Tanzania. The claim payment data for the period of 2001–2021 from NHIF were used in building the ARIMA model. It was proven that ARIMA (0, 2, 2) is the most accurate model for forecasting the claim payments from 2022 to 2031. Furthermore, numerical results show that the claim payments for NHIF will grow by 68% by 2031.
The Environmental Kuznets Curve of Guangdong Province

The assumption of Environmental Kuznets and its inverted-U curve,which tells that the environmental quality will be deteriorated and then improved along with the economic growth,is introduced.It is also analyzed how the inverted-U curve is formed.The environmental quality will not be improved automatically except by interference of environmental policies.Based on the experimental analysis of Guangdong Province,the relationship between economy and environment is examined,by using the emission data of wastewater,waste gas,COD_(Cr) and SO_2 into modeling.It shows that the emission is accelerated in the past twenty years and the emission of some pollutants is near the turning point,which means that the emission would decrease with the economic growth.The improved environmental performance is due to the enhanced integrated environmental control in the last five years.
THE LOVEDAY BASIN: SALINITY, ACIDITY, WATER CHEMISTRY, ISOTOPE GEOCHEMISTRY, MINERALOGY, BIOLOGY AND SQUISHY MUD

INTRODUCTION The Loveday Basin was previously a natural flooded wetland adjacent to the River Murray. However, in the last three decades, this site was used as a disposal basin for saline water, which led to increased salinization of the site and also the accumulation of sulfur-rich sediments. This has led to certain environmental problems, in particular noxious smells produced from the reduced S compounds, and as such, the Loveday Basin has been selected by the Murray-Darling Basin Commission to be the test case for remediation. The purpose of the project is to characterize the physical, chemical and biological properties of sediment and water at the site and to determine how these will change upon the wetting and drying of the area. Results of this work will then be used by land managers to determine remediation strategies.
Video-based sympathetic arousal assessment via peripheral blood flow estimation

Electrodermal activity (EDA) is considered a standard marker of sympathetic activity. However, traditional EDA measurement requires electrodes in steady contact with the skin. Can sympathetic arousal be measured using only an optical sensor, such as an RGB camera? This paper presents a novel approach to infer sympathetic arousal by measuring the peripheral blood flow on the face or hand optically. We contribute a self-recorded dataset of 21 participants, comprising synchronized videos of participants’ faces and palms and gold-standard EDA and photoplethysmography (PPG) signals. Our results show that we can measure peripheral sympathetic responses that closely correlate with the ground truth EDA. We obtain median correlations of 0.57 to 0.63 between our inferred signals and the ground truth EDA using only videos of the participants’ palms or foreheads or PPG signals from the foreheads or fingers. We also show that sympathetic arousal is best inferred from the forehead, finger, or palm.
A 0.079-pJ/b/dB 32-Gb/s 2× Half-Baud-Rate CDR Circuit With Frequency Detector

A 32-Gb/s <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> half-baud-rate (THBR) clock and data recovery (CDR) circuit is presented by using a phase detector (PD) and a frequency detector (FD). The frequency detection range of the FD is analyzed. This prototype is fabricated in a 28-nm CMOS process with an active area of 0.055 mm2. The measured frequency capture range is 43.7% for a 32-Gb/s pseudorandom bit sequence (PRBS) of 27-1. This proposed CDR circuit achieves a bit error rate of less than <inline-formula> <tex-math notation="LaTeX">$10^{-12}$ </tex-math></inline-formula> under the channel loss of 23 dB at 16 GHz. The total power consumption is 58.6 mW at 32 Gb/s and achieves a figure-of-merit (FoM) of 0.079 pJ/bit/dB.
LSSVM-CC: ensemble algorithm of color constancy using least square support vector machine

Abstract. Color constancy (CC) refers to the ability to reproduce the veritable color of objects by eliminating the influence of environmental illumination. The performance of CC has been greatly boosted by advanced learning-based methods, such as deep neural networks. However, most current deep learning methods suffer from large model sizes and large-scale training datasets for promising performance. We propose least square support vector machine-CC (LSSVM-CC), an efficient CC method using LSSVM, which combines preferably unitary statistics-based methods to achieve better illuminant estimation performance at low computation efforts with small training samples. The core of our LSSVM-CC is to cluster training images based on illumination-preferred features and then train an ensemble model using LSSVM for each cluster, which can effectively improve the overall performance. Once trained, our LSSVM-CC selects adaptive models for different input images to perform accurate illuminant estimation in the testing phase. Experiments on typical benchmark datasets show that our method significantly outperforms most traditional statistics-based methods and is also comparable to some sophisticated and computationally demanding learning-based methods.
Exploring the antecedents of trust and users’ continuance intention in hybrid online travel platforms: the role of network externalities and platform quality

ABSTRACT Drawing from network externalities perspective in the Economics literature, this study investigates the antecedents of trust and users’ continuance intention in the context of hybrid online travel platforms (HOTPs). Data were obtained by surveying 489 users of HOTPs in China. The empirical results based on the PLS-SEM model showed that indirect and direct network externalities positively influence functional quality and hedonic quality respectively. Furthermore, both functional quality and hedonic quality of HOTPs positively affect users’ trust, which in turn positively affects users’ continuance intention and negatively affects perceived risks.
Trajectory Correction of the Rocket for Aerodynamic Load Shedding Based on Deep Neural Network and the Chaotic Evolution Strategy With Covariance Matrix Adaptation

This article studies the problem of trajectory correction optimization for aerodynamic load shedding in the rocket's ascending phase considering the wind. Based on the statistical horizontal wind field, the weakest wind field is proposed to plan the nominal trajectory and the strongest wind field is proposed to test the performance of the designed trajectory. Considering the weakest wind field, two time-varying correction coefficients are calculated by one deep neural network unlike the traditional methods, and used to plan the rocket's flight attitudes when optimizing the rocket's trajectory. There are a large number of parameters to be optimized in this problem, so the traditional trajectory optimization techniques may suffer from poor convergence issues. By introducing the chaotic function into the traditional evolution strategy with covariance matrix adaptation, a novel variant C-CMA-ES is proposed to solve the trajectory optimization problem, and its efficiency is demonstrated by some popular test functions. Besides, the cost function to be minimized is shaped based on the rocket's maximal normal aerodynamic load and final state deviations. Finally, compared with the other three strategies, the efficiency of the proposed trajectory correction strategy is demonstrated by multiple simulation scenarios considering the strongest wind field and the Monte Carlo method considering the random wind fields.
Habitat Use and Diet Composition of the Common Eland (Tragelaphus oryx) in Ngorongoro Conservation Area, Tanzania

Ngorongoro Conservation Area (NCA) is renowned worldwide for its multiple land use where pastoralism and wildlife conservation co-exist. Thus, the NCA must meet a delicate balance of competing needs between livestock and wildlife. Currently the NCA is conducting resettlement program to facilitate pastoralists who are willing to move and resettle outside of the conservation area in order to reduce the number of people and livestocks in NCA. The common eland (Tragelaphus oryx) are among the large herbivore species found in the NCA that might be affected by possible competition between livestock and wildlife. The information on this species including habitat utilization and feeding ecology is limited. This study therefore, investigated the factors influencing habitat use and diet composition of the common eland (Tragelaphus oryx) in NCA. Data were collected along 82 pre-established transects using direct field survey. The study therefore assessed habitat use, distribution patterns, diet composition and conservation threats facing the common eland in NCA, The results indicated that the grassland habitat was mainly used by elands (> 85% in both dry and wet seasons), while other habitats were least used (< 15%). Eland diet composition varied significantly among plant species, with the animals most frequently feeding on Themeda triandra but rarely on Vachellia tortilis and Hibiscus aponeurus. The study concludes with recommendations for enhancement of grassland habitat management and reduced anthropogenic activities to enhance eland conservation in NCA.
Profile of functioning of Brazilian children with congenital Zika syndrome: a longitudinal study applying the common brief ICF core set for cerebral palsy

ABSTRACT To use the International Classification of Functioning, Disability and Health (ICF) to investigate whether children with congenital Zika Syndrome (CZS) show changes in their functioning and disability profile after nine months. This study included children with CZS recruited from a support centre for children with microcephaly in Brazil. The children's functional abilities and limitations were classified using ICF Core Set for children with cerebral palsy. Each ICF category was quantified in two moments with a mean interval of nine months. The study included 81children (mean age = 38.4 ± 3.3mo). Most children showed changes between assessments. Categories that presented improvements were in body functions (five categories), environmental factors (two categories), and activity and participation (one category) sections. Most children with CZS evaluated improved their functioning and disability profile over time, mainly in body functions. These changes can be related to the course of the disease or to the health programmes that children had access.
Identifying the promising production planning and scheduling method for manufacturing in Industry 4.0: a literature review

ABSTRACT Industry 4.0 technologies create a connected ecosystem that allows for real-time monitoring, control, and optimization. This enables the manufacturing industry to move the ultimate goal of their businesses from lean to leagile. Then, to meet the needs of leagile manufacturing, an integrated production planning and scheduling system is needed. The academic world responds to the need by the growth of papers. Many methodologies, models, frameworks, and methods have been proposed. Literature abounds on classifying them, yet it remains inconclusive mainly on their applicability to Industry 4.0. In this regard, this paper conducts a literature review aiming to show the state of the art and discover the most promising production planning and scheduling method for Industry 4.0 among the many. Lastly, on the basis of this study, recommendations on possible future research directions are provided for researchers, and the design of the next-generation production planning and scheduling system for Industry 4.0 is also suggested.
RESPONSE OF N2O TO NITROGEN MANAGEMENT AND BREEDING FOR SEED OIL IN BIODIESEL DEDICATED CANOLA

While breeding for increased oil yield has generated new lines of spring canola (Brassica napus L.) for biodiesel production, emissions of N2O from fertilized canola fields threaten to undermine the climate change mitigation benefits of canola as a biodiesel alternative to conventional diesel. This study determined the response of N2O emissions to canola line and N treatment in a maritime setting (Truro, Nova Scotia). Tissue N uptake was measured to determine whether differences in N uptake between the lines could explain any observed effect of canola line. Nitrate Exposure (the summation of daily soil NO3- concentrations over a growing season, serving as an integrated measure of the exposure of soil biomass to nitrate over the growing season) was determined to investigate its potential as a predictor of N2O emissions. Four spring canola lines (‘Topaz’, ‘Sentry’, ‘Polo’, and 04C204, in order of increasing seed oil content) were paired with five N treatments (40, 60, 80, 100, and 120 kg N ha-1) in an incomplete two-factor factorial design over two growing seasons (2008 and 2009). N2O emissions were determined using a non-steady state vented chamber method. N2O emissions peaks closely followed increases in soil water content in both years, indicating that limited aerobicity was the trigger for N2O emissions events, and suggesting that denitrification was the predominant microbial process responsible for N2O emissions. The magnitude of average N2O emissions both years was considerably low when compared to other studies (0.55 and 0.56 kg N2O ha-1 in 2008 and 2009 respectively). Increasing N treatment resulted in significantly increased N2O emissions in 2008. Though the same trend was observed in 2009, it was not found to be significant. Differences in weed cover, soil C, soil N supplying capacity, and elevation between the sites may have contributed to the inability to detect an N2O emissions response to N treatment in 2009. Canola line had no effect on N2O emissions in either study year, though heavy competition by weeds significantly affected canola plant health and survival in 2009. Tissue N uptake increased with increasing N treatment, but did not change with choice of line, which is consistent with the observation of no N2O emissions response to line. Nitrate Exposure was found to be strongly correlated with N2O emissions in a linear relationship, supporting the conclusion that Nitrate Exposure can be a promising indicator of N2O emissions when they are limited by soil N. Finally, FluxPerOil, the ratio of N2O emissions per unit oil yield (kg N2O kg-1 oil) was found to decrease with decreased N treatment in 2008, though only very little, indicating a marginal abatement of N2O emissions at a significant cost of oil. FluxPerOil was unreliable in 2009 due to weeds compromising the line effect and therefore oil yield.
The Effects of Photosynthetic Characters and Water Use Efficiency under Drought Stress in Sugarcane Materials

The photosynthetic characters and water use efficiency were measured under drought stress with six sugarcane materials planted in pots.The results showed that net photosynthetic rate,transpiration rate and stomatal conductance all decreased,but intercellular CO2 concentration and water use efficiency had different change tendency with the increasing of drought stress time.There was higher correlation among photosynthetic traits in different sugarcane materials.ROC22 and S.spontaneum L.performed to be highly resistant to drought.Fruit Sugarcane and KN90-445 performed middle resistance.S. robustum Brandes et Jeswiet ex Grassl and ROC16 performed to be poor resistant to drought.