Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of ammonia loading on lysine utilization by growing cattle

Six ruminally-cannulated Holstein steers (202 ± 15 kg) were used to study the effects of ruminal ammonia loading on whole-body lysine utilization. Steers were housed in metabolism crates and used in a 6 × 6 Latin square design. All steers received 2.52 kg of DM/d of a diet (10.1% CP) containing 82% soybean hulls, 8% wheat straw, 5% cane molasses, and 5% vitamins and minerals. Ten g/d of urea was infused continuously into the rumen of all steers to ensure adequate ruminal ammonia concentrations; concurrently, steers were ruminally infused continuously with 200 g/d acetic acid, 200 g/d propionic acid, and 50 g/d of butyric acid and abomasally infused with 300 g/d of glucose continuously to increase energy supply without increasing microbial protein supply. Steers were also abomasally infused continuously with an excess of all essential amino acids except lysine to ensure that lysine was the only limiting amino acid. Treatments were arranged as a 3 × 2 factorial with 3 additional levels of urea (0, 40, or 80 g/d) continuously infused ruminally to induce ammonia loading and 2 levels of lysine (0 or 6 g/d) continuously infused abomasally. Treatments did not affect fecal N output (P = 0.37). Lysine supplementation decreased (P < 0.01) urinary N excretion from 51.9 g/d to 44.3 g/d, increased (P < 0.01) retained N from 24.4 to 33.3 g/d, and tended (P = 0.09) to reduce plasma urea-N. Urea infusions linearly increased retained N (26.7, 28.8, and 31.1 g/d; P = 0.05) and also linearly increased (P < 0.01) urinary N excretion (31.8, 48.1, and 64.4 g/d), urinary urea (21.9, 37.7, and 54.3 g/d), urinary ammonia (1.1, 1.4, and 1.9 g/d), and plasma urea (2.7, 4.0, and 5.1 mM) for 0, 40, and 80 g urea/d, respectively. Assuming that retained protein is 6.25 × retained N and contains 6.4% lysine, the incremental efficiencies of infused lysine utilization were 51, 59, and 69% for steers receiving 0, 40, and 80 g/d of urea, respectively, suggesting that the ruminal ammonia loads might improve the efficiency of lysine utilization; this is supported by the observed increases in whole-body protein deposition in response to ammonia loading of our steers that were, by design, lysine deficient.
for the Special Theme: ‘The Big 5 Trends in ICT’ An Examination of Social Media Practices that Improve Customer Satisfaction in the B2B Market in the ICT Sector in India

: Recent developments in Information and Communication Technology (ICT) have initiated significant transformation in the way in which B2B firms interact with existing and potential customers. These advancements have a profound impact on the marketing practices of firms. Social media is one of the most important information technology tools which have a transformative impact on business enterprises. It has dramatically influenced businesses and industries in this era. Social connectivity through this online platform has become a key to marketing in firms. Given the exponential increase in the use of social media, firms need to be present where their customers are in order to know the needs of their customers and to satisfy them. The use of social media as a component of a firms’ marketing strategy is widely recognised by marketing practitioners. Also, marketers have embraced the abilities of these online platforms to assist in marketing practices in firms. However, there is limited research that explores the influence of social media usage on customer satisfaction in the B2B sector. This study seeks to fill this gap and examines the influence of social media practices adopted by the ICT firms on customer satisfaction. A web based survey was used to collect data from a sampling frame of ICT firms in India. Analysis shows that social media practices have a positive and significant influence on customer satisfaction. This research makes a distinct contribution to social media literature. It addresses the gap in literature by providing an understanding of the effective use of social media for marketing purposes by the B2B firms in the ICT sector in India. It provides empirical evidence to support that these effective social media practices improves customer satisfaction in these firms.
Characterizing Small-scale Farmers Differential Vulnerability to Global Environmental Change: Case Studies in Anger Watershed, Southwestern Ethiopia

Purpose: Global environmental change of climate variability and land use dynamics are emerging livelihood challenges facing local poor. Although, the synergetic impacts of these processes have been cognate in Ethiopia, vulnerability researches were fixed to climate variability, inadequate on conceptual and methodological considerations of non-climate stressors. To this attention, we assessed small-scale farmers’ vulnerability situations in Anger watershed of southwestern Ethiopia. Methods: The case study design guided by mixed methods approach was used. Multistage sampling technique was used for the study. The data collected from 335 household heads were analyzed by multivariate analysis, measures of differences, and substantiated by qualitative enquiry based on focus group discussions and observations. Result: Household’s vulnerability magnitude ranges from high to moderate, while in aggregate, kolla agroecology was more vulnerable than highland. The effects of social adaptability and sensitivity to land resources were significantly contributed for the vulnerability differences. Although, climate variability was notable, structural land use dynamics was unequivocal stressor deepened the household’s vulnerability in kolla. Conclusions: Vulnerability is the result of interactive and interconnected processes of climate, non-climate stressors, and households’ internal capacity in the study area. Thus, attributing local vulnerability to only climate variability, neglecting local non-climatic disturbances could mislead development planning. Hence, future studies should consider such processes simultaneously to provide comprehensive evidences on vulnerability situations. The national adaptations program needs to integrate climate change with the emerging other global changes in planning rural resilience. Policy fortifying agricultural investments should synchronize win-win strategy for relationships between investors and local community.
When conflicting interests meet-A critical study of the collaboration and ideals in the project BoStad2021

​Decision-makers in Gothenburg face major challenges in solving the housing shortage. As a response, the housing project BoStad2021 has been initiated by public and private actors with the goal of constructing 7,000 new homes before 2021. Currently, we live in an era of urban entrepreneurialism according to David Harvey, indicating that many cities are primarily driven by economic growth through, for example, public-private partnerships rather than safeguarding the welfare interests of the inhabitants. The purpose of this article is to investigate to what extent BoStad2021 can be understood through the lens of urban entrepreneurialism. I focus on collaboration, including tensions and conflicts, and the physical ideals actors work toward in the project. Apart from the theory of urban entrepreneurialism I also make use of Jane Jacobs’ critique of modernist design and Daniel Aldrich's theory of the siting of controversial facilities. Accordingly, the study fills a knowledge gap since urban entrepreneurialism most often is concerned with the inner city. A critical analysis was conducted by data from interviews with involved actors such as politicians, officials, and constructors alongside documents such as BoStad2021's website, follow-up research on the project and detailed development plans. The results show that the public-private interests in BoStad2021 do not simply overlap and align, as initially appeared and is the norm in urban entrepreneurialism, but in this case the municipality outdoes the construction companies in line with its own public agenda by wanting to invest and risk more than the latter and does therefore not simply serve the economic development. However, in line with urban entrepreneurialism the actors work toward inner-city ideals such as small-scaleness, urbanity and densification in the peripheral areas as well, which in the long run risks leading to exclusion and gentrification.
A Survey on Text Pre-Processing & Feature Extraction Techniques in Natural Language Processing

– Natural Language Processing (NLP) is a subset of AI that deals with the way machines understand and interpret human Language. Everything that a computer understands is in the form of numbers rather than words. It is therefore worthwhile to study what preprocessing and feature extraction techniques need to be implemented on a human language such that when it is converted to numbers its meaningful enough for the computer to interpret it. One of the major NLP tasks is Text Classification which has found its importance in many use cases such as web search, document classification, chatbots, virtual assistants and so on. Unstructured sentences or texts are inherently difficult to convert to a machine understandable format. Special importance has been given to Pre-processing techniques as they form a precursor on the later stages of information retrieval strategies. Any error in the initial preprocessing techniques is propagated to the later stages of NLP pipeline. Also, the choice and order of the techniques such as tokenization, StopWords removal, lemmatization are carefully studied. Information retrieval systems are particularly concerned with how well the textual data are cleaned and filtered to remove noisy data that do not contribute to increasing the efficiency and moreover lead to erroneous results. This Survey paper emphasizes on the importance of the efficient use of text preprocessing techniques along with Information retrieval using feature extraction techniques of Natural Language Processing.
EMPOWERING WOMEN AT THE HIGHER INSTITUTIONAL LEVEL: ANALYSIS OF BUSINESS EDUCATION AND LEADERSHIP TRAINING PROGRAM

Purpose – The research study aims to assess the women’s Business education and leadership training program at a higher institutional level in order to examine how the program impacts and contributes to women’s empowerment. Further, this research sought to explore women’s leadership training aspect that has not explicitly elucidated. Besides, this study looks upon women’s self-perception by empowering them with skills and leadership capabilities to change hard-core gender stereotypes in society. Research methodology – The sample size comprised of 82 enrolled female students in the training program. The qualitative statistics (i.e., three focus groups) evaluated with the Kirkpatrick model. The Wilcoxon signed-rank test was applied to compare pre-and post-training quantitative data (i.e., questionnaire). Effect size is measured to check the effectiveness of the training program. Findings – The post-training evaluation revealed higher scores in knowledge, tools, and leadership skills. The training program encouraged women to bring change in self-perception and gain confidence for transformative changes in society. Findings support the effectiveness of leadership education and training programs. Research limitations – This research conducted in a Pakistani patriarchal cultural context and one region of Pakistan (Punjab). Hence the results are carefully generalised. The long term outcomes of this leadership training program and women’s performance in the job market are not studied. Practical implications – Findings suggest that a training program positively affects women’s learning, knowledge, and behaviour. Training programs empower women with practical tools for self and business development. The program encouraged women to gain better insight into work-life challenges and enhance personal competencies to gain equal rights. Originality/Value – This research will significantly contribute to the relatively scarce literature on the effectiveness of women’s business education and leadership training programs at a higher institutional level in the Pakistani context for women empowerment.
ASSESSING MOMENTARY USER EXPERIENCE WITH CONVERSATIONAL AGENTS USING AN ELECTROENCEPHALOGRAPHY DEVICE

All User Experience aspects can play a part in eliciting feelings about a certain product. Momentary UX refers to any changes of feelings during the interaction at the moment it happens. To be able to evaluate Momentary UX, electrophysiological measures have been used. The aim of this study is to compare Momentary UX episodes while participants interacted with different conversational agents. Thirty-six participants of both genders were divided into three groups to perform the same tasks. First group was the control group using Google’s search engine in Google’s Chrome browser; the second group used Google’s Assistant using keyboard and the third used Google’s Assistant using voice commands. An Emotiv Insight device and UX questionnaires were used to collect data. The results between groups from both the electroencephalogram and questionnaires were consistent and differences were discussed. There was difference in the user’s Momentary UX regarding their excitement levels collected by the EEG when they were interacting with conversational agents by voice. The main contribution is using electroencephalography as a instrument to measure Momentary UX and inferring that the interaction using voice shows emotional particularities.
Application of Seismic Waveform Classification to Reservoir Characterization of Kamalapuram Formation: A case study from Cauvery Basin, India

Enormous efforts have been made for establishing a reliable relationship between Geophysical parameters and subsurface geology. Integration of these data along with well information would greatly enhance our understanding of subsurface geology leading to reservoir characterization. This would further help in reducing uncertainties in all the phases of upstream activities ranging from exploration to production. The Kamalapuram Formation of Eocene age in Madanam area gained prominence with the discovery of hydrocarbons from two wells and other leads. Characterizing these sands have been challenging owing to their discrete nature and thin pay zones. Potential of reservoir can be realized once the nature of facies along with habitat of hydrocarbons is determined. The seismic signature of these sands is often composite in nature. An ideal waveform carries with it an inherent information of frequency, amplitude & phase and the changes in these attributes help us to understand the variation in lithology or the impact of pore fluid. The play is of strati structural nature with varying thickness and lithology; hence a waveform based approach for characterizing these sands is appropriated. The waveform based study has an advantage over amplitude attributes as it provides an enhanced objectivity to the interpreter. A neural network based waveform classification supervised by well information has been carried out to generate a Seismic Facies map. The results are calibrated with wells and are validated by good hydrocarbon shows in recently drilled wells. This study has thus helped us in deciphering the sand distribution and would provide great assistance in further exploration and development phases in this area.
Negatively curved Einstein metrics on ramified covers of closed four-dimensional hyperbolic manifolds

— This paper is a shortened version of the recent article Examples of compact Einstein four-manifolds with negative curvature [11] written in collaboration with J. Fine (ULB). Its content was presented by the author at the Séminaire de Théorie Spectrale et Géométrie in Grenoble in December 2017. In [11], new examples of compact, negatively curved Einstein manifolds of dimension 4 have been obtained. These are seemingly the first such examples which are not locally homogeneous. The Einstein metrics we construct are carried by a sequence of 4-manifolds (Xk), previously considered by Gromov and Thurston [13], and obtained as ramified coverings of closed hyperbolic 4-manifolds. Our proof relies on a deformation procedure. We first find an approximate Einstein metric on Xk by interpolating between a model Einstein metric near the branch locus and the pull-back of the hyperbolic metric from the base hyperbolic manifolds. We then perturb to a genuine solution to Einstein’s equations, by a parameter dependent version of the inverse function theorem.
Dynamics of Robots

The subject of this chapter is the dynamic analysis of robots modeled using the Newton-Euler method, one of several approaches for deriving the governing equations of motion. It is assumed that the robots are characterized as open kinematic chains with actuators at the joints that can be controlled. The kinematic chain consists of discrete rigid members or links, with each link attached to neighboring links by means of revolute or prismatic joints, i.e., lower-pairs (Denavit and Hartenberg, 1955). One end of the chain is fixed to a base (inertial) reference frame and the other end of the chain, with an attached end-effector, tool, or gripper, can move freely in the robotic workspace and/or be used to apply forces and torques to objects being manipulated to accomplish a wide range of tasks. Robot dynamics is predicated on an understanding of the associated kinematics, covered in a separate chapter in this handbook. An approach for robot kinematics commonly adopted is that of a 4 × 4 homogeneous transformation, sometimes referred to as the Denavit-Hartenberg (D-H) transformation (Denavit and Hartenberg, 1955). The D-H transformations essentially determine the position of the origin and the rotation of one link coordinate frame with respect to another link coordinate frame. The D-H transformations can also be used in deriving the dynamic equations of robots.
In Vitro Gastrointestinal Digestibility and Antioxidant Activity of Fermented Millet

摘要:以小米酸肉中辅料小米为研究对象,分析辅料小米餐后血糖变化及模拟胃肠消化过程中消化率、粒经变化及抗氧化活性 的变化。 结果表明:随餐后时间的延长,血糖值在 0~30 min 时先增加,大于 30 min 迅速降低,餐后 240 min 时血糖值为 22.79 dl/mg 基本稳定,与 300 min 时血糖值 23.42 dl/mg 无显著差异(p<0.05),样品在分别经口腔、胃、小肠消化的过程中,随消化过程的进行 产物粒经逐渐减小,蛋白质及脂肪消化率逐渐增加,消化至胃肠阶段时蛋白质消化率为 69.45%、脂肪消化率为 29.88%,在抗氧化试 验中,随消化的进行多酚及多肽含量显著增加(p<0.05),最高为 6.06 mg/100 g,多肽含量最高为 5.21 mg/mL;随消化的进行抗氧化 能力逐渐增加,消化液中-OH 自由基清除率最大值为 81.63%、DPPH 自由基清除率最大值为 78.12%、ABTS 清除率最大值为 7.62%。 综合分析,辅料小米较小米对照样品餐后血糖偏低,蛋白质、脂肪消化率高,同时辅料小米多酚、多肽含量及抗氧化活性(-OH 及 DPPH 自由基清除率、ABTS 清除率)均比小米对照样品高,为小米发酵类产品的开发提供基础,而对小米发酵类产品营养健康方面
Association between opioid receptor gene polymorphism and postoperative pain response in Koreans

Received: August 10, 2012. Revised: August 24, 2012. Accepted: September 14, 2012. Corresponding author: Seung Ho Choi, M.D., Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, 250, Seongsan-ro, Seodaemun-gu, Seoul 120-752, Korea. Tel: 82-2-2228-2429, Fax: 82-2-312-7185, E-mail: csho99@yuhs.ac Background: The objective of this study was to investigate the association between A118G single nucleotide polymorphism (SNP) of human μ-opioid receptor (OPRM1) gene and the postoperative pain response in Korean patients undergoing thyroidectomy. Methods: Fifty two adult patients undergoing thyroidectomy were enrolled in this study. Their blood samples were genotyped for the A118G polymorphism. Pain intensity was assessed by a verbal numerical rating scale (VNRS) at postanesthesia care unit, postoperative 6, 24, and 48 hours. Mechanical pain threshold was assessed using electronic von Frey preoperatively and repeated at postoperative 24 and 48 hours on the forearm and periincisional regions. Results: Of the 50 patients, 23 patients were A118 homozygous (AA), 19 patients were heterozygous (AG), and 8 patients were 118G homozygous (GG). The VNRS score was higher in patients with GG genotype than other genotypes at PACU (P < 0.05). Mechanical pain thresholds on the forearm and periincisional area were decreased at postoperative 24 and 48 hours from the preoperative values in all genotypes (P < 0.05). However, the changes in pain thresholds were similar among the genotypes. Conclusions: A118G SNP of OPRM1 gene is associated with inter-individual difference in immediate postoperative pain score in Korean population. (Anesth Pain Med 2012; 7: 343∼347)
Characterization of the CsI(Tl) Crystalline Scintillating Detector Produced at IPEN

Cesium iodide crystal activated with thallium (CsI(Tl)) is used as radiation sensor because of its favorable characteristics as scintillator, when excited by gamma radiation. This crystal has good mechanical strength and it is relatively little hygroscopic. In the present work, the CsI(Tl) crystal was grown in the Nuclear Energy Research Institute (IPEN/CNEN/SP) by Brigdman technique, in two different formats: (a) cylindric (∅ 20.1 mm x  11.9 mm) and (b) parallelepiped ( 12.3 mm x  19.5 mm). The scintillator spectrometry was studied through five gamma radiation sources: Tc (140 keV), Ba (355 keV) Na (511 keV) and Cs (662 keV). The crystals were coupled to a photomultiplier tube using 0.5 McStokes viscosity silicone grease as the optical interface. All electronics for signal measurements were developed at IPEN. Luminescence property of the CsI(Tl) crystal was excited by the radiation from a Cs source. The energy resolution of the crystalline detector was determined by the FWHM parameter, corresponding to the photopeak width at half of its height.
Formation of a cooperation network in Mato Grosso on Machine Learning and Image Analysis: Diagnosis of COVID-19 in X-ray images

Since the beginning of the COVID-19 outbreak, the scientific communityhas been making efforts in several areas, either by seekingvaccines or improving the early diagnosis of the disease to contributeto the fight against the SARS-CoV-2 virus. The use of X-rayimaging exams becomes an ally in early diagnosis and has been thesubject of research by the medical image processing and analysiscommunity. Although the diagnosis of diseases by image is a consolidatedresearch theme, the proposed approach aims to: a) applystate-of-the-art machine learning techniques in X-ray images forthe COVID-19 diagnosis; b) identify COVID-19 features in imagingexamination; c) to develop an Artificial Intelligence model toreduce the disease diagnosis time; in addition to demonstrating thepotential of the Artificial Intelligence area as an incentive for theformation of critical mass and encouraging research in machinelearning and processing and analysis of medical images in the Stateof Mato Grosso, in Brazil. Initial results were obtained from experimentscarried out with the SVM (Support Vector Machine) classifier,induced on a publicly available image dataset from Kaggle repository.Six attributes suggested by Haralick, calculated on the graylevel co-occurrence matrix, were used to represent the images. Theprediction model was able to achieve 82.5% accuracy in recognizingthe disease. The next stage of the studies includes the study of deeplearning models.