Miracle-dz/UniFAR-FTUs huggingface dataset:
Journal of Agric. 2020 Vol. 20 No.1& 2

Nigerian indigenous chickens possess immunity from endemic diseases and have a better survival rate than commercial hybrid strains under local production conditions. FUNAAB Alpha chicken was developed by improving Nigerian indigenous chickens through crossbreeding and selection. This study compared the mitochondrial d-loop of FUNAAB Alpha and Nigerian indigenous chickens to check likely genetic erosion and loss of diversity in development of FUNAAB Alpha breed. Blood samples were collected from Nigerian indigenous (n=23) and FUNAAB Alpha (n=20) chickens sampled from farms and houses in Ogun state, Nigeria. The Hypervariable 1 (HV1) of the mitochondrial d-loop region was amplified and sequenced. Single nucleotide polymorphisms present in HV1 of chickens were identified using Clustal W. Genetic diversity of the region was determined using DnaSp v5 while selective forces acting on the chickens were predicted using HyPhy software implemented inside MEGA 6 software. Phylogenetic relationship among FUNAAB Alpha, Nigerian indigenous and other chicken breeds was determined using MEGA 6 software. Five polymorphisms were identified in FUNAAB Alpha chickens while twelve were identified in Nigerian indigenous chickens. All the polymorphisms identified in FUNAAB Alpha chickens were also observed in Nigerian indigenous chickens while seven polymorphisms were unique to Nigerian indigenous chickens. Higher diversity indices were observed in Nigerian indigenous chickens (number of haplotype: 4; haplotype diversity: 0.743±0.012; nucleotide diversity: 0.014±0.0013 and average number of nucleotide differences: 4.332) compared with FUNAAB Alpha chickens (number of haplotype: 2; haplotype diversity: 0.485±0.001; nucleotide diversity: 0.008±0.0001 and average number of nucleotide differences: 2.424). Positive selective forces were acting on FUNAAB Alpha chickens while negative selective forces were acting on Nigerian indigenous chickens. Phylogenetic analysis revealed that FUNAAB Alpha chickens clustered with Nigerian indigenous and South American chickens. It can be concluded that there was likely genetic erosion and loss of diversity in development of FUNAAB Alpha breed. Breeding programmes aimed at improvement of genetic diversity and reduction of genetic erosion should be applied in subsequent improvement of FUNAAB Alpha chickens.
Bpr Implementation in Europe: The Adaptation of a Management Concept

This paper analyses Business Process Re-engineering (BPR) implementation in 20 European firms. In contrast with the radical postulates of the early orthodox literature, the find- ings reveal that BPR was used in a preventive way, with implementation time lengths directly related to the scope of the organisational changes attempted and generating moderately positive results according to corporate performance indicators, with relatively low social cost.
Tunnel Heading Stability in Drained Ground

When considering ground conditions for tunnelling one might distinguish between ground with and without a macro structure due to stratification, schistosity and jointing. In this study attention is focused on soils and very soft rock without a significant macro structure. These materials tend to be encountered for shallow tunnelling in urban areas, whereas macro-structured ground is dominant in deep tunnelling. For soils and very soft rock, as considered in this study, stability is governed by shear strength parameters that can be measured in laboratory tests. For soft soils with little (effective) cohesion, it is necessary to drive the tunnel using a shield. For soils or rock with greater cohesion, it is possible to use an open face tunnelling method such as the NATM. Here, if necessary the stability of the tunnel face can be improved by inclining the face or by reducing the cross section of the excavation. In this study we will consider face stability both for closed-face shield tunnelling and openface NATM tunnelling. When discussing previous research on tunnel heading stability, one has to distinguish between drained and undrained conditions. For undrained conditions, as dominant in clays, practical design curves have been derived on the basis
Study of low frequency noise in scaled down silicon CMOS transistors

Summary form only given. A detailed investigation of the low frequency (LF) noise in 0.25 /spl mu/m NMOS and PMOS devices is carried out. A theoretical analysis of the drain current noise and the gate voltage noise characteristics is developed in the framework of a carrier number fluctuation model as well as corrected mobility fluctuations. The scattering parameter is found to be lower for NMOS transistors, while the value of PMOS is relatively high, in agreement with static mobility data. This justifies the enhancement of the correlated mobility noise for PMOS devices.
IRM - when it works and when it doesn't: A test case of natural language inference

Invariant Risk Minimization (IRM) is a recently proposed framework for out-of-distribution (o.o.d) generalization. Most of the studies on IRM so far have focused on theoretical results, toy problems, and simple models. In this work, we investigate the applicability of IRM to bias mitigation—a special case of o.o. d generalization—in increasingly naturalistic settings and deep models. Using natural language inference (NLI) as a test case, we start with a setting where both the dataset and the bias are synthetic, continue with a natural dataset and synthetic bias, and end with a fully realistic setting with natural datasets and bias. Our results show that in naturalistic settings, learning complex features in place of the bias proves to be difﬁcult, leading to a rather small improvement over empirical risk minimization. Moreover, we ﬁnd that in addition to being sensitive to random seeds, the performance of IRM also depends on several critical factors, notably dataset size, bias prevalence, and bias strength, thus limiting IRM’s advantage in practical scenarios. Our results highlight key challenges in applying IRM to real-world scenarios, calling for a more naturalistic characterization of the problem setup for o.o. d generalization.
Yield potential of world wheat based on ARIMA model under global warming

As the most important food crop across the world, with continuous increase in world population and steady declining farmlands, wheat has been attracting academic attention for improving its yield or potential in the future particularly under global warming. Therefore, analyzing the yield or potential of wheat at global level relevant to greenhouse gas effect is of great significance to direct future production of wheat in the world. However up to now, there are relatively few reports on potential yield of world wheat projected using ‘time series’ approach like ARIMA (Auto-regressive Integrated Moving Average) model. Thus in this paper, the crop potential yield of world wheat during 2019 to 2028 is projected using ARIMA model based on the yields from 1961 to 2018. Our results show that during 2019 to 2028, the average yields of world wheat are projected to increase from 3569 to 4257 kg ha-1 while top yields of world wheat from 9852 to 11246 kg ha-1. Annual global mean temperatures are projected to increase from 15.05 to 15.31°C. Global warming exerts positive effect on average yield of world wheat while negative effect on the top yield in 1961 to 2018 and 2028. Our study concluded that for world wheat production in 2019 to 2028, the opportunities for improving production should be mainly dependent on the advantage of highyield countries as the yield is still in low place before the turn-point of S-shaped curve in long-term trend affected partly by greenhouse gas effect.
Influence of prevailing weather parameters on population dynamics of spotted stem borer, Chilo partellus (Swinhoe) and its natural enemies on maize in Haryana

The experiment was conducted at CCS Haryana Agricultural University Regional Research Station, Karnal to ascertain the influence of prevailing meteorological parameters on population dynamics of Chilo partellus and its natural enemies on maize during Kharif, 2017. Maximum oviposition (0.75 egg masses per plant) was recorded during 28 th standard meteorological week (SMW) whereas larval population was at peak during 31st SMW (3.8 larvae per plant). Cumulative (47.5%) and fresh plant infestation (11.5%) were maximum during 34 th and 28 th SMW, respectively. Maximum egg parasitisation (6.53%) by Trichogramma sp. and larval parasitisation (31.64%) by Cotesia flavipes was recorded during 28th and 33rd SMW, respectively. Changes in pest population were correlated and regressed with weather parameters. Egg and larval populations of C. partellus and parasitisation by Trichogramma sp. exhibited significant positive correlation with average minimum temperature whereas C. flavipes exhibited significant negative correlation with average maximum temperature (r = -0.741) and highly significant positive correlation with evening relative humidity (r = 0.695). Plant infestation and dead heart formation were significantly correlated with average minimum temperature and non-significantly correlated with all other weather parameters. The multiple linear regression analysis explained the variability due to various weather parameters. This information can be utilised while formulating integrated management tactics against this pest.
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond

To train networks, lookahead algorithm [1] updates its fast weights k times via an inner-loop optimizer before updating its slow weights once by using the latest fast weights. Any optimizer, e.g. SGD, can serve as the inner-loop optimizer, and the derived lookahead generally enjoys remarkable test performance improvement over the vanilla optimizer. But theoretical understandings on the test performance improvement of lookahead remain absent yet. To solve this issue, we theoretically justify the advantages of lookahead in terms of the excess risk error which measures the test performance. Speciﬁcally, we prove that lookahead using SGD as its inner-loop optimizer can better balance the optimization error and generalization error to achieve smaller excess risk error than vanilla SGD on (strongly) convex problems and nonconvex problems with Polyak-Łojasiewicz condition which has been observed/proved in neural networks. Moreover, we show the stagewise optimization strategy [2] which decays learning rate several times during training can also beneﬁt lookahead in improving its optimization and generalization errors on strongly convex problems. Finally, we propose a stagewise locally-regularized lookahead (SLRLA) algorithm which sums up the vanilla objective and a local regularizer to minimize at each stage and provably enjoys optimization and generalization improvement over the conventional (stagewise) lookahead. Experimental results on CIFAR10/100 and ImageNet testify its advantages. Codes is available at https://github.com/sail-sg/SLRLA-optimizer .
INFANT HOSPITAL LIBRARY: Case Study in a Brazilian Public Hospital

The child, when hospitalized, loses the freedom to play, as he is accustomed to, for being confined in a hospital environment, subject to a medical treatment that can cause pain and fear. The adult who accompanies needs information about the disease and the treatment of the child. The infant hospital library attempts to meet the needs of both of its users. However, such a library has not been thoroughly considered for scientific inquiry. Hence, this paper investigates its structure and actions by addressing three subjects as follows. First, a software was developed specifically for this type of library, which registered the catalog, users and loans data of two years of service of a voluntary infant hospital library in a Brazilian state public hospital. Then, an exploratory study of the reading preferences of the users while hospitalized was carried out, whose findings follow. Adults play an important role in encouraging and assisting recreational reading, which occurred in all age groups of a child and similarly between genders. Furthermore, users preferred to read literature, religious and comic books in their native language that generally consist of short stories. Finally, collection development policies were determined based on the users’ reading preferences.
Framework for managing uncertainty in property projects

A primary task of property development (or real estate development, RED) is making assessments and managing risks and uncertainties. Property managers cope with a wide range of uncertainties, particularly in the early project phases. Although the existing literature addresses the management of calculated risks, the management of uncertainties is underexposed. A framework and method are presented for uncertainty management, both of which focus on the early phases of complex RED projects. To develop this method, a design method for the development of consumer-based software (SCRUM) is adapted. The traditional uncertainty management in property development was compared with the SCRUM approach. SCRUM is found to be a highly useful tool for uncertainty management in real estate, but it requires adjustment to the specific context of property. An adjusted method ‘RESCRUM’ was developed and a first test of its accuracy and usefulness in practice is presented. Une des tâches principales des promoteurs immobiliers consiste à évaluer et à gérer les risques et les incertitudes. La profession est confrontée à des incertitudes nombreuses et variées, notamment lors des premières phases d'un projet. Bien que la littérature spécialisée traite de la gestion des risques calculés, la gestion des incertitudes reste insuffisamment étudiée. Cet article présente un cadre et une méthode de gestion des incertitudes, qui se concentrent sur les premières phases d'un projet immobilier complexe. Pour développer cette méthode, on a étudié le développement d'un logiciel basé sur le consommateur (SCRUM). La gestion classique des incertitudes dans le cadre du développement immobilier est comparée à l'approche SCRUM. Cette approche s'avère être un outil très utile pour la gestion des incertitudes dans l'immobilier mais elle nécessite des adaptations au contexte spécifique de la propriété. Une méthode ajustée appelée RESCRUM a été mise au point et un premier test de sa précision et de son utilité pratique est présenté. Mots clés: processus de conception, approche du processus, gestion de projet, promotion immobilière, gestion des risques, gestion des incertitudes, collaboration
Understanding the Multiple Factors Determining of Generation Z to Hotel Staycation During Covid-19 Pandemic

The impact of the Covid-19 pandemic on restricted mobility and a devastating economic development in various sectors has changed renewed interest in the future of tourism, especially in the Hospitality Industry. This study sought to examine the Theory of Planned Behavior in the context of hotel staycation during the Covid-19 pandemic. Paired t-tests and the structural equation modelling were applied to assess the 230 responses of Generation Z in Indonesia for the first and second quarters of 2021. The finding showed that attitude, perceived behavioural control, and subjective norms affect the hotel staycation intention during a pandemic for Z generations. Perceived behavioural control plays the most significant part. Several findings are provided on how the generation perceives travelling during the COVID-19 pandemic and encourage them to resume travelling after the travel restriction is lifted. Theoretical and practical implications are discussed. The viewpoint proffered in this study provides scopes of the hospitality industry in terms of hotel staycation programs to maintain a resilient economic strategy during the pandemic.
Flow resistance of wastewater pumping mains

A key requirement for the effective and economic design of sewer pumping stations is reliable information on the flow resistance of pipes carrying wastewater. The hydraulic resistance of such pipes can depend on a variety of factors, including the thickness of the biological slimes that build up in the pipe walls over a period of time, the size of the pipe, the velocity of the flow and characteristics of the sewage being pumped through the system. Current knowledge on this problem is limited and, therefore, a field study was undertaken of 16 pumping mains to collect data on in-service flow resistance. Data from each site were analysed to determine the hydraulic resistance of the pumping mains and the importance of parameters such as flow velocity and pipe diameter. It was found that the most important parameter affecting the hydraulic resistance in wastewater pumping mains is the flow velocity: as the flow velocity increases the hydraulic resistance decreases. Other parameters such as pipe material and di.
PERCUTANEOUS MITRAL COMMISUROTOMY DURING PREGNANCY: 246 CASES

Objective: This work aims at studying the indications and immediate to long term results of percutaneous mitral commisurotomy during pregnancy. Methods: A retrospective study of 246 mitral valve dilations performed during pregnancy from 1997 to 2018 in the Cardiology A department, Ibn Sina Teaching hospital Rabat. We analyzed clinical, echocardiographic and hemodynamic data before and after PMC: Results: Our patients’ mean age was 28 ± 5.2 years and the gestational age 28.1 ± 4 weeks of amenorrhea. Mitral stenosis was discovered during pregnancy in 40% of cases and all 246 patients were primiparous. 94% of our patients were symptomatic (NHYA stages III to IV). 85% of patients had sinus rhythm. On cardiac ultrasound imaging, mitral stenosis was severe in all our patients: mean surface area of 0.8cm2 and ≤ 1cm2 in 85% of our cases; 90% of our patients had Wilkins’ score of 8 – 9. Mean transvalvular gradient was high (21.4mmHg) and most of our patients had pulmonary hypertension (mean Pulmonary Artery systolic pressure 71mmHg). The procedure had 98% success rate with immediate regression of symptoms to NYHA stages I to II in 95% cases. After PMC, pregnancy reached full term in 95% of our patients with low fetal morbimortality and delivery in good conditions, mostly vaginal (85% of our cases). Conclusion: PMC is the ideal treatment for severe symptomatic mitral stenosis during pregnancy, yielding excellent results with very few complications. It leads to a clear regression of symptoms and improves hemodynamic parameters as well as pregnancy and delivery conditions. When indicated, PMC should be performed in a reference centre.
Ascidian diversity of Costa Rica, including new records for the North Pacific

Introduction: The class Ascidiacea has about 3 000 species, which fulfill various roles in the ecosystem, for example, they filter high amounts of particles, and are shelter and food for other animals. Furthermore, the group has a high number of invasive species reported. In Costa Rica, ascidians have been barely studied. Objective: In this study, we aim to describe the diversity of ascidians in Costa Rica from new samplings in Área de Conservación Guanacaste, North Pacific, and by compiling previous reports for the entire country in order to improve the group’s state of knowledge. Methods: Samples were collected during two field trips between 2018 and 2019, at six sites within the Gulf of Santa Elena and three sites near the Murcielago Islands area. The specimens were dissected and analyzed in detail to determine the species. All the identifications were compared with the available information from literature and from museum collections. Literature, collections databases of the National Museum of Natural History, Smithsonian Institution and the new material collected were used to create an updated taxonomic list. Results: A total of eight species were obtained from 70 specimens. Of these, five are new reports for the country, which increase to 22 species the total number reported for Costa Rica. The most common species was Rhopalaea birkelandi, whose presence was higher in Santa Elena Bay. Conclusions: This study improved the knowledge of ascidian diversity in Costa Rica. Polyandrocarpa anguinea, reported for the first time, is considered invasive in other areas, which suggests the necessity of a continuous monitoring of its population. It is necessary to include more areas of the country since almost all the reported species come from the North Pacific; the diversity of ascidians from other parts of the country, especially the Caribbean, is still unknown.
Back-Projection Algorithm Optimization for On-Board Embedded SAR Imaging System

The Synthetic Aperture Radar (SAR) is a type of radar capable of high-resolution coherent Imaging. To produce images from SAR data, an image forming algorithm must be used. The Backprojection Algorithm is known for generating high resolution images at the expense of computational intensity. Due to this drawback, the Backprojection Algorithm has never been widely adopted for real time applications or implementation in Small, Weight and Power (SWaP) devices. The first contribution of this work is the analysis and fixed-point conversion of the Backprojection Algorithm while providing high-quality images. The second key contribution of this work is the implementation of the Backprojection algorithm in a System-on-Chip (SoC) Field Programmable Gate Array (FPGA) device. A proof of concept was done on a Zybo Z7-10 board where it was observed the resulting 512x512 image had a signal-to-noise ratio of 99.21 dB. This result was achieved in 959ms, representing a speedup of 500x over the original software implementation.
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning

Current transfer learning algorithm designs mainly focus on the similarities between source and target tasks, while the impacts of the sample sizes of these tasks are often not sufficiently addressed. This paper proposes a mathematical framework for quantifying the transferability in multi-source transfer learning problems, with both the task similarities and the sample complexity of learning models taken into account. In particular, we consider the setup where the models learned from different tasks are linearly combined for learning the target task, and use the optimal combining coefficients to measure the transferability. Then, we demonstrate the analytical expression of this transferability measure, characterized by the sample sizes, model complexity, and the similarities between source and target tasks, which provides fundamental insights of the knowledge transferring mechanism and the guidance for algorithm designs. Furthermore, we apply our analyses for practical learning tasks, and establish a quantifiable transferability measure by exploiting a parameterized model. In addition, we develop an alternating iterative algorithm to implement our theoretical results for training deep neural networks in multi-source transfer learning tasks. Finally, experiments on image classification tasks show that our approach outperforms existing transfer learning algorithms in multi-source and few-shot scenarios.