Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of short time precise dietary energy–protein in reproductive parameters of local crossbred dairy goats

Objective: This study aimed to establish and focus on the implications of precise energy and protein levels on reproductive performance. This study based on field facts showed that excessive feed intake, especially protein intake, to increase productivity will lead to some decreased reproductive efficiency through disruption of reproductive hormonal compound biosynthesis or increasing blood urea nitrogen (BUN), which has rarely been studied. Materials and Methods: Healthy and mature Saanen crossbred goats raised by traditional farmers (2–4 years old; ± 45 kg) were divided into three experimental groups [T0 = basal feed according to the feed provided by farmers, T1 = protein and energy balanced feed according to National Research Council (NRC) (±5%), T2 = feed >20% excess protein, and excess energy from NRC] (n = 75). The factorial method was used in the experimental design with a post-hoc least significant difference test. Results: The data showed a significant difference (p < 0.05) in the biochemical or hormonal parameters between the control and the treatment groups. Also, T1 showed leads in any blood profile and reproductive hormone parameters such as total protein (79.6 ± 5.3 gm/dl), cholesterol (3.26 ± 0.47 mmol/l), progesterone (1.79 ± 2.21 ng/ml), and estrogen (47.85 ± 5.51 pg/ml), as well as the lowest levels of BUN (11.6 ± 1.59 mmol/l) and cortisol (25.07 ± 14.85 ng/ml) levels. T1 had the highest reproductive potential after treatment. Conclusion: The adverse effects of high and low protein consumption on reproductive hormones seem to be related to the blood profile and ovarian function, as hormone concentrations change significantly and lead to reproductive impairment. The data showed that balanced nutrient levels (5%/T1) resulted in excellent blood and hormone parameters.
Research of Auto-Disturbances-Rejection Suspension Algorithm Based on Magnetic Flux Feedback

The auto-disturbances-rejection suspension algorithm based on magnetic flux feedback has been brought up in this paper. The magnetic flux signal is not given by sensors, but it comes from nonlinear ESO (Extended State Observer). The nonlinear ESO designed in this paper has good dynamic characters that are only determined by the poles’ place of the compensated matrix. There is no relation between the dynamic characters and the format of nonlinear function. The experiment and simulation results denote that the new suspension control method designed in this has some advantages.
Home Automation Using ARM-7 Microcontroller with Improved Security

The Internet of Things (IoT) is a next-generation technology that enables easy remote control of home appliances and offers people a simple and convenient lifestyle. Home automation system based on ARM7 and IoT technology infrastructure (ARM7, communication devices, NodeMCU) enables remote control without human intervention. Home automation is a major advancement in technology that allows you to control lighting, security, temperature, alarms and appliances. This study presents the development of three modules that allow homeowners to remotely monitor readings with their mobile devices. The modules include dust monitoring, house light activation and gas sensors. Each module contains a microcontroller and a sensor that records the data and transmits it over the Internet, ultimately producing a report. The mobile app interprets the data and provides a readable report that homeowners can use to make future decisions. In summary, this study shows the potential of IoT and home automation systems to enable efficient and convenient control of various home appliances and devices, providing a better lifestyle for homeowners.
A varying coefficient approach to estimating hedonic housing price functions and their quantiles

ABSTRACT The varying coefficient (VC) model introduced by Hastie and Tibshirani [26] is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coefficients are allowed to vary as smooth functions of an effect modifier possibly different from the regressors. The VC model reduces the modelling bias with its unique structure while also avoiding the ‘curse of dimensionality’ problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modelling to the estimation of a hedonic house price function using data from Hong Kong, one of the world's most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modelling with quantile regression to examine the heterogeneity of the marginal effects of attributes across the distribution of housing prices.
Effects of Different Soil Moisture Contents on Photosynthesis of Lettuce

In order to explore the photosynthetic physiological response characteristics of lettuce under different soil moisture conditions, the photosynthetic indexes and chlorophyll fluorescence parameters of lettuce under different soil moisture gradients were determined by pot water control experiment. The results showed that with the decrease of soil moisture content, Pn, Tr, Gs, Ci, Fv/Fm, ΦPSII and qP of lettuce leaves all showed a downward trend, while NPQ increased with the decrease of soil moisture content. Among them, the water holding capacity in the field was 55~60%, and the net photosynthetic rate of lettuce was the highest, indicating that mild drought promoted photosynthesis of lettuce.
Numerical investigation using an exact solution of the effects of non-solenoidality of the viscous terms on the incompressible flow

We examine effects of the divergence of the viscous terms on the numerical results of an incompressible flow by using an exact solution of the governing equation. When the Poisson equation is solved using fractional steps, the divergence in the velocity field may have nonzero magnitude. It should be noted that the divergence of the viscous terms can be larger than that of the velocity field. We use an exact solution, which is commonly used for benchmarking, to examine the effects of the divergence of the viscous terms. The divergence of the viscous terms affects the equilibrium relations found in the exact solution. In the present numerical results, the divergence of the viscous terms reduces the rate of decay of the kinetic energy and the pressure, and it also causes some harmonic waves in the flow field. We examine these results quantitatively by using approximations to the numerical results. Skewness and kurtosis factors of the physical quantities are also affected by the divergence of the viscous terms. These results show that the divergence of the viscous terms significantly affects the flow field.
Unraveling the Mystery of Fever Source: The Vital Role of Physical Examination in Hospitalized Patients With Emphasis on Peripheral Line-Associated Bloodstream Infections

Fever in hospitalized patients requires timely identification of the underlying cause for appropriate treatment. While laboratory tests and imaging studies are valuable, the significance of physical examination should not be overlooked. We present a case of peripheral line-associated bloodstream infection that was readily diagnosed through physical examination during an infectious disease consultation for fever of unknown origin. It is important for busy physicians to prioritize physical examinations to prevent diagnostic errors. Prompt and focused physical examinations contribute to improved patient outcomes and the prevention of healthcare-associated infections.
Spectropolarimetry of the BL-Ic SN 2014ad

Abstract Over the past two decades a clear relation between Gamma-Ray Bursts (GRBs) and some broad-lined Type Ic Supernovae (SNe) has been observed. The use of spectropolarimetry allows us to directly probe the 3D geometry of the unresolved ejecta of SNe, which can help us better understand the physics of their explosion and the SN-GRB connection. We present 7 epochs of spectropolarimetry of the broad-lined Type Ic SN 2014ad and highlight its similarities with SN 1998bw.
Scene Flow Estimation from RGBD Images

This thesis addresses the problem of reliably recovering a 3D motion field, or scene flow, from a temporal pair of RGBD images. We propose a semi-rigid estimation framework for the robust computation of scene flow, taking advantage of color and depth information, and an alternating variational minimization framework for recovering rigid and non-rigid components of the 3D motion field. Previous attempts to estimate scene flow from RGBD images have extended optical flow approaches without fully exploiting depth data or have formulated the estimation in 3D space disregarding the semi-rigidity of real scenes. We demonstrate that scene flow can be robustly and accurately computed in the image domain by solving for 3D motions consistent with color and depth, encouraging an adjustable combination between local and piecewise rigidity. Additionally, we show that solving for the 3D motion field can be seen as a specific case of a more general estimation problem of a 6D field of rigid motions. Accordingly, we formulate scene flow estimation as the search of an optimal field of twist motions achieving state-of-the-art results.
Terahertz wave interaction with metallic nanostructures

Abstract Understanding light interaction with metallic structures provides opportunities of manipulation of light, and is at the core of various research areas including terahertz (THz) optics from which diverse applications are now emerging. For instance, THz waves take full advantage of the interaction to have strong field enhancement that compensates their relatively low photon energy. As the THz field enhancement have boosted THz nonlinear studies and relevant applications, further understanding of light interaction with metallic structures is essential for advanced manipulation of light that will bring about subsequent development of THz optics. In this review, we discuss THz wave interaction with deep sub-wavelength nano structures. With focusing on the THz field enhancement by nano structures, we review fundamentals of giant field enhancement that emerges from non-resonant and resonant interactions of THz waves with nano structures in both sub- and super- skin-depth thicknesses. From that, we introduce surprisingly simple description of the field enhancement valid over many orders of magnitudes of conductivity of metal as well as many orders of magnitudes of the metal thickness. We also discuss THz interaction with structures in angstrom scale, by reviewing plasmonic quantum effect and electron tunneling with consequent nonlinear behaviors. Finally, as applications of THz interaction with nano structures, we introduce new types of THz molecule sensors, exhibiting ultrasensitive and highly selective functionalities.
Physico-Chemical Characteristics of Gomti River at Lucknow Stretch,India.

Nuzhat Parveen This study was aimed to determine the current status of river Gomti along the Lucknow stretch. Physico-chemical characteristics, level of organic matter, various heavy metals and sewage pollution and their variation has been studied from upstream to downstream of Lucknow. Gaughat is upstream region and Pipraghat is downstream of Lucknow. The samples are taken from upstream to downstream regions of the river. Water samples are subjected to analysis like Total Solids, Total Dissolved Solids, Total Suspended Solid, Conductivity, pH, COD, BOD and DO. Study concluded that large number of drains are responsible for pollution in river Gomti that enter directly into the river carrying untreated industrial and domestic waste. Some other causes are like removal of solid wastes at pumping stations is still manual, sometimes pumping station does not work ,so the sewage waste is by passed directly to the river Gomti or when most of the branch and trunk sewers do not function properly. Study indicates that the water quality has been deteriorated from Gaughat to Pipraghat due to discharge of untreated waste water from about 26 major drains in its entire course. Water of the river Gomti at upstream of Lucknow i.e. Gaughat showed minimum BOD and maximum dissolved oxygen. But due to the presence of 26 drains dissolved oxygen level decreases along its stretch and showed minimum DO at Pipraghat.
Association of postural education and postural hygiene with low back pain in schoolchildren: Cross-sectional results from the PEPE study

Background: Low back pain (LBP) is the leading cause of disability in the world that affects the population of all ages globally. The main aim of the present study was to analyze the cross-sectional association of postural education and postural hygiene habits with LBP, differentiating between frequency and intensity of pain. Methods: This cross-sectional study assessed 849 students aged 10-12 years from primary schools. The study was based on four different structured and self-administered questionnaires: back pain questionnaire, Back Pain and Body Posture Evaluation Instrument (BackPEI), Frequency of Commuting to and from School Questionnaire, and the Hebacaknow questionnaire. In addition, height and weight were included to determine the body mass index (BMI). Results: Participants with prevalence of LBP were significantly older (P=0.038), girls (P<0.001), taller (P=0.018), and practice active travelled back from school (P=0.016). Otherwise, participants with no prevalence of LBP sat correctly at the desk (P<0.001). Higher knowledge of postural education was associated with lower intensity of LBP (β=-0.07, CI=-0.12 – -0.02, P=0.004). Conclusion: The knowledge related to postural education it is associated with less LBP. School interventions improving knowledge about postural education, ergonomics and postural hygiene are needed to address this important matter.
The phenotypic diversity in the production performance of Alabio ducks (Anas platyrhynchos Borneo) in South Kalimantan, Indonesia

Objective: This study aimed to examine the diversity of phenotypic characteristics of female Alabio ducks (Anas platyrhynchos Borneo) and their eggs in South Kalimantan, Indonesia. Materials and Methods: A total of 200 18-month-old ducks and 300 eggs were selected using a survey method with multistage random sampling. These samples were obtained from two districts in the province of South Kalimantan [Banjar (BJ) districts and Tanah Laut (TL)]. The observed data were analyzed descriptively with variations using the independent t-test for each location. Principal component analysis (PCA) was deployed to assess the overall variance and define variables with greater discriminatory power between individuals. Results: The observations on the body’s physical characteristics and the eggs of Alabio ducks showed significant differences between ducks from BJ and TL areas (p < 0.05) except for yolk diameter, albumen height, albumen index, and Haugh unit (HU) (p > 0.05). Most egg quality traits from BJ were greater than those from TL, which include egg weight, egg length, egg width, yolk weight, albumen weight, shell weight, shell thickness, and egg shape index. The PCA revealed medium-to-high communalities in the phenotypic body characteristics of Alabio ducks and their eggs. Conclusion: Significant physical characteristics and egg quality differences were found between the two locations, except for the albumen index and HU, with substantial variability within each trait. These traits could explain the total variation in the phenotypic characteristics of female Alabio ducks.
The nutritional value of Spirulina and utilization research

With the development of modern society, the demand for nutrition, health, and food safety among people is also increasing. More and more consumers are connecting their diet to a healthy lifestyle in order to reduce the occurrence of chronic diseases. Spirulina, known as green ginseng, is one of the most productive microalgae with high output value. It is considered as one of the most ideal dietary supplements due to its unique nutritional and health benefits. The main components of spirulina include protein, fat, vitamins, chlorophyll, and minerals. The protein content is particularly high, ranging from 60–70%. Spirulina can be used as a natural nutritional supplement, providing various essential nutrients needed by the body. Apart from being a nutritional supplement, spirulina is also widely utilized in the food, medicine, and cosmetics industries. Spirulina powder can be added to various foods such as bread, cakes, and biscuits to enhance their nutritional value. Spirulina extract can also be used in the production of healthcare and beauty products. Furthermore, the antioxidant and immune-boosting effects of spirulina make it a promising natural medicine for research in the treatment of cancer and liver disease. This paper aims to provide comprehensive information on the nutritional composition, secondary metabolites, and biological activities of spirulina, thereby contributing to the spirulina industry.
FAKE NEWS DETECTION USING NATURAL LANGUAGE PROCESSING

Online social media plays an important role during real world events such as natural calamities, election s, social movements etc. Since the social media usage has increased, fake news has grown. The social media is often used by modifying true news or creating fake news to spread misinformation. The creation and distribution of fake news poses major threats in several respects from a national security point of view. Hence Fake news identification becomes an essential goal for enhancing the trustworthiness of the information shared on online social network. Over the period of time many researcher has used different methods, algorithms, tools and techniques to identify fake news content from online social networks. The aim of this paper is to review and examine these methodologies, different tools, browser extensions and analyze the degree of output in question. In addition, this paper discuss the general approach of fake news detection as well as taxonomy of feature extraction which plays an important role to achieve maximum accuracy with the help of different Machine Learning and Natural Language Processing algorithms. Keywords—Fake News Detection, Natural Language Processing, Online Social Network, Machine Learning, Sentiment Analysis.
Molecular counting of membrane receptor subunits with single-molecule localization microscopy

We report on quantitative single-molecule localization microscopy, a method that next to super-resolved images of cellular structures provides information on protein copy numbers in protein clusters. This approach is based on the analysis of blinking cycles of single fluorophores, and on a model-free description of the distribution of the number of blinking events. We describe the experimental and analytical procedures, present cellular data of plasma membrane proteins and discuss the applicability of this method.
LAProof: A Library of Formal Proofs of Accuracy and Correctness for Linear Algebra Programs

The LAProof library provides formal machine-checked proofs of the accuracy of basic linear algebra operations: inner product using conventional multiply and add, inner product using fused multiply-add, scaled matrix-vector and matrix-matrix multiplication, and scaled vector and matrix addition. These proofs can connect to concrete implementations of low-level basic linear algebra subprograms; as a proof of concept we present a machine-checked correctness proof of a C function implementing sparse matrix-vector multiplication using the compressed sparse row format. Our accuracy proofs are backward error bounds and mixed backward-forward error bounds that account for underflow, proved subject to no assumptions except a low-level formal model of IEEE-754 arithmetic. We treat low-order error terms concretely, not approximating as $\mathcal{O}\left( {{u^2}} \right)$.
Directing Job Search in Practice: Mandating Pay Information in Job Ads *

Using a policy reform that mandated firms to provide pay information in job ads, I study how workers adapt their search behavior and firms their hiring decisions, including actual wages. At the time of the reform, only one fifth of job ads contained pay information, strongly varying across firms and occupations. Linking online job board data to administrative social security data, I find that wages of newly hired workers increased, by about 3%, particularly within complying firms that were induced by the reform to show pay information. Job ads posted by these firms received more clicks and applications from job-seekers but I do not find evidence that the wage increase was driven by a positive selection of employees: previous wages of newly hired workers at their prior job did not increase, and additionally, applicants had on average lower pay expectations and characteristics less fitting job ads requirements. Furthermore, I do not find evidence of closing the gender pay gap. Adapting a simple model of partial job search, I illustrate how to interpret these responses.
Computer Algebra for Lattice path Combinatorics

Classifying lattice walks in restricted lattices is an important problem in enumerative combinatorics. Recently, computer algebra has been used to explore and to solve a number of difficult questions related to lattice walks. We give an overview of recent results on structural properties and explicit formulas for generating functions of walks in the quarter plane, with an emphasis on the algorithmic methodology.
Effective Models of new physics at the Large Hadron Collider

With the start of the Large Hadron Collider runs, in 2010, particle physicists will be soon able to have a better understanding of the electroweak symmetry breaking. They might also answer to many experimental and theoretical open questions raised by the Standard Model. Surfing on this really favorable situation, we will first present in this thesis a highly modelindependent parametrization in order to characterize the new physics effects on mechanisms of production and decay of the Higgs boson. This original tool will be easily and directly usable in data analysis of CMS and ATLAS, the huge generalist experiments of LHC. It will help indeed to exclude or validate significantly some new theories beyond the Standard Model. In another approach, based on model-building, we considered a scenario of new physics, where the Standard Model fields can propagate in a flat six-dimensional space. The new spatial extra-dimensions will be compactified on a Real Projective Plane. This orbifold is the unique six-dimensional geometry which possesses chiral fermions and a natural Dark Matter candidate. The scalar photon, which is the lightest particle of the first Kaluza-Klein tier, is stabilized by a symmetry relic of the six dimension Lorentz invariance. Using the current constraints from cosmological observations and our first analytical calculation, we derived a characteristic massrange around few hundred GeV for the Kaluza-Klein scalar photon. Therefore the new states of our Universal Extra-Dimension model are light enough to be produced through clear signatures at the Large Hadron Collider. So we used a more sophisticated analysis of particle mass spectrum and couplings, including radiative corrections at one-loop, in order to establish our first predictions and constraints on the expected LHC phenomenology