Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Dietary Oil Type and Energy Intake in Lactating Sows on the Fatty Acid Profile of Colostrum and Milk, and Piglet Growth to Weaning

Simple Summary Substituting soya oil with salmon oil in lactation diets improved sow milk yield and litter gain during the suckling period. Additionally, salmon oil tended to reduce pre-weaning mortality; therefore, its use in lactation diets should be further investigated. A phased dietary energy regimen increased sow lactation energy intake, but sow body condition and piglet growth performance to weaning were not improved. Abstract This study investigated the effect of salmon oil in lactating sow diets and offering these diets in a phased dietary regimen to increase the energy density of the diet in late lactation. Sow and piglet productivity to weaning, the fatty acid profile of milk, piglet blood and tissues at weaning were the main parameters measured. Multiparous sows (n = 100) (Landrace × Large White) were offered dietary treatments from day 105 of gestation until weaning. Dietary treatments (2 × 2 factorial) included oil type (soya or salmon oil) and dietary regimen (Flat 14.5 MJ/kg DE diet offered until weaning or Phased 14.5 MJ/kg DE diet offered to day 14 of lactation then a second diet containing 15.5 MJ/kg DE offered from day 15 until weaning). Salmon oil inclusion increased the total proportion of n-3 fatty acids in colostrum (p < 0.001), milk (p < 0.001), piglet plasma (p < 0.01), adipose (p < 0.001), liver (p < 0.001) and muscle (p < 0.001). Increasing sow dietary energy level in late lactation increased the total n-3 fatty acids in milk (p < 0.001), piglet adipose (p < 0.01) and piglet muscle (p < 0.05). However, piglet growth to weaning did not improve.
The ATLAS Tile Calorimeter performance in the LHC Run 2 and its upgrade towards the High-Luminosity LHC

The Tile Calorimeter (TileCal) is a sampling hadronic calorimeter covering the central region of the ATLAS experiment. The TileCal uses steel as the absorber and plastic scintillators as the active medium. The scintillators are read out by wavelength shifting fibres coupled to photomultiplier tubes (PMTs). The analogue signals from the PMTs are amplified, shaped, digitized by sampling the signal every 25 ns, and stored on detector until a trigger decision is received. The TileCal front-end electronics reads out the signals produced by about 10k channels measuring energies ranging from about 30 MeV to about 2 TeV. Each stage of the signal production from scintillation light to the signal reconstruction is monitored and calibrated. A summary of the performance results using proton-proton collisions from LHC Run 2 at 13 TeV is presented. The High-Luminosity phase of the LHC, delivering up to 7.5 times the LHC nominal instantaneous luminosity, is expected to begin in 2026. The TileCal will require new electronics to meet the requirements of a 1 MHz trigger, higher ambient radiation, and to ensure better performance under high pileup conditions. Both the onand off-detector TileCal electronics will be replaced during the shutdown of 2024-2025. PMT signals from every TileCal cell will be digitized and sent directly to the back-end electronics, where the signals are reconstructed, stored, and sent to the first level of trigger at a rate of 40 MHz. This will provide better precision for calorimeter signals used by the trigger system and will allow the development of more complex trigger algorithms. Changes to the electronics will also contribute to the data integrity and reliability of the system. The ongoing developments for onand off-detector systems, together with expected performance characteristics and recent results of test-beam campaigns with the electronics prototypes are discussed.
Effects of a Non-Thermal Atmospheric Pressure Plasma Jet with Different Gas Sources and Modes of Treatment on the Fate of Human Mesenchymal Stem Cells

Despite numerous attempts to use human mesenchymal stem cells (hMSCs) in the field of tissue engineering, the control of their differentiation remains challenging. Here, we investigated possible applications of a non-thermal atmospheric pressure plasma jet (NTAPPJ) to control the differentiation of hMSCs. An air- or nitrogen-based NTAPPJ was applied to hMSCs in culture media, either directly or by media treatment in which the cells were plated after the medium was exposed to the NTAPPJ. The durations of exposure were 1, 2, and 4 min, and the control was not exposed to the NTAPPJ. The initial attachment of the cells was assessed by a water-soluble tetrazolium assay, and the gene expression in the cells was assessed through reverse-transcription polymerase chain reaction and immunofluorescence staining. The results showed that the gene expression in the hMSCs was generally increased by the NTAPPJ exposure, but the enhancement was dependent on the conditions of the exposure, such as the source of the gas and the treatment method used. These results were attributed to the chemicals in the extracellular environment and the reactive oxygen species generated by the plasma. Hence, it was concluded that by applying the best conditions for the NTAPPJ exposure of hMSCs, the control of hMSC differentiation was possible, and therefore, exposure to an NTAPPJ is a promising method for tissue engineering.
Comparison between implanted Si and NTD-Ge thermistors performance in AgReO4 microcalorimeters for a new neutrino mass experiment

We report here the preliminary results of the R&D for a new neutrino mass experiment. This experiment is prepared in the framework of the Microcalorimeters Arrays for a Rhenium Experiment (MARE) project. First tests were made on silicon implanted and germanium NTD arrays with AgReO4 crystals. r 2005 Elsevier B.V. All rights reserved. PACS: 07.20. Fw; 29.40. n; 23.40. Bw; 14.60. Pq
Effects of parecoxib sodium intervention before induction on inflammatory stress response and endocrine steady state after laparoscopic surgery

Effects of parecoxib sodium intervention before induction on inflammatory stress response and endocrine steady state after laparoscopic surgery Yu-Qiang Su, Zhong-Lei Zheng, Jing Li, Jing Liu, Xiao-Ying Fan 1. Anesthesiology Department, the Second Affiliated Hospital of Xi’an Medical University in Shaanxi Province, Xi’an City, Shaanxi Province, 710038 2. Outpatient Office, the Second Affiliated Hospital of Xi’an Medical University in Shaanxi Province, Xi’an City, Shaanxi Province, 710038 Journal of Hainan Medical University
INDUCTION OF RESIDUAL STRESSES AND INCREASE OF SURFACE HARDNESS BY MACHINE HAMMER PEENING TECHNOLOGY

Machine Hammer Peening is a novel technology for surface treatment, which is based on an actuator that can be attached to any kind of machine tool. This actuator moves an axially guided hard metal ball with an oscillating movement to a work piece surface. The main positive effects of the treatment are the induction of compressive residual stresses, the hardness increase of the upper surface layer and a reduction of surface roughness. Also, a controlled and defined structuring of a material surface is possible by the use of this technology. The purpose of this paper is to show, how this novel technology can be used to influence the surface and the upper surface layer of a material for compressive residual stresses and surface hardening. The X-ray diffraction method and the hole drilling method were used to measure the residual stresses. A comparison of both investigation results is done as part of this work. The results of all investigations show a hardness increase of the upper surface layer.
Multiple Instance Learning for Emotion Recognition Using Physiological Signals

The problem of continuous emotion recognition has been the subject of several studies. The proposed affective computing approaches employ sequential machine learning algorithms for improving the classification stage, accounting for the time ambiguity of emotional responses. Modeling and predicting the affective state over time is not a trivial problem because continuous data labeling is costly and not always feasible. This is a crucial issue in real-life applications, where data labeling is sparse and possibly captures only the most important events rather than the typical continuous subtle affective changes that occur. In this work, we introduce a framework from the machine learning literature called Multiple Instance Learning, which is able to model time intervals by capturing the presence or absence of relevant states, without the need to label the affective responses continuously (as required by standard sequential learning approaches). This choice offers a viable and natural solution for learning in a weakly supervised setting, taking into account the ambiguity of affective responses. We demonstrate the reliability of the proposed approach in a gold-standard scenario and towards real-world usage by employing an existing dataset (DEAP) and a purposely built one (Consumer). We also outline the advantages of this method with respect to standard supervised machine learning algorithms.
First dominating non-thermal pressures by CPA-laser pulses in contrast to billion degree thermal pressures for fusion

The experiment by Steinke et al. proves that sub-picosecond CPA laser pulses produce energy densities above 10 12 J/cm 3 for generation of non-thermal, nonlinear-force driven pressures that are much higher in contrast to the thermal pressures above 50Million o C temperatures usually needed for fusion energy in power reactors.
Keller-Box Simulation for the Buongiorno Mathematical Model of Micropolar Nanofluid Flow over a Nonlinear Inclined Surface

Brownian motion and thermophoresis diffusions are the fundamental ideas of abnormal upgrading in thermal conductivity via binary fluids (base fluid along with nanoparticles). The influence of Brownian motion and thermophoresis are focused on in the Buongiorno model. In this problem, we considered the Buongiorno model with Brownian motion and thermophoretic effects. The nonlinear ordinary differential equations are recovered from the partial differential equations of the boundary flow via compatible similarity transformations and then employed to the Keller-box scheme for numerical results. The physical quantities of our concern including skin friction, Nusselt number, and Sherwood number along with velocity, temperature and concentration profile against involved effects are demonstrated. The impacts of the involved flow parameters are drawn in graphs and tabulated forms. The inclination effect shows an inverse relation with the velocity field. Moreover, the velocity profile increases with the growth of the buoyancy effect.
An MVA Vector Expressing HIV-1 Envelope under the Control of a Potent Vaccinia Virus Promoter as a Promising Strategy in HIV/AIDS Vaccine Design

Highly attenuated poxviral vectors, such as modified vaccinia virus ankara (MVA), are promising vaccine candidates against several infectious diseases. One of the approaches developed to enhance the immunogenicity of poxvirus vectors is increasing the promoter strength and accelerating during infection production levels of heterologous antigens. Here, we have generated and characterized the biology and immunogenicity of an optimized MVA-based vaccine candidate against HIV/AIDS expressing HIV-1 clade B gp120 protein under the control of a novel synthetic late/early optimized (LEO) promoter (LEO160 promoter; with a spacer length of 160 nucleotides), termed MVA-LEO160-gp120. In infected cells, MVA-LEO160-gp120 significantly increased the expression levels of HIV-1 gp120 mRNA and protein, compared to the clinical vaccine MVA-B vector expressing HIV-1 gp120 under the control of the commonly used synthetic early/late promoter. When mice were immunized with a heterologous DNA-prime/MVA-boost protocol, the immunization group DNA-gp120/MVA-LEO160-gp120 induced an enhancement in the magnitude of gp120-specific CD4+ and CD8+ T-cell responses, compared to DNA-gp120/MVA-B; with most of the responses being mediated by the CD8+ T-cell compartment, with a T effector memory phenotype. DNA-gp120/MVA-LEO160-gp120 also elicited a trend to a higher magnitude of gp120-specific CD4+ T follicular helper cells, and modest enhanced levels of antibodies against HIV-1 gp120. These findings revealed that this new optimized vaccinia virus promoter could be considered a promising strategy in HIV/AIDS vaccine design, confirming the importance of early expression of heterologous antigen and its impact on the antigen-specific immunogenicity elicited by poxvirus-based vectors.
Leeds University Business School THE ANNOUNCEMENT EFFECT OF CASH DIVIDEND: EVIDENCE FROM TURKISH CAPITAL MARKET

This study analyses the announcement effect of cash dividends on share prices in the Turkish capital markets. It is investigated whether cash dividend announcements result in an abnormal return around the announcement day in Istanbul Stock Exchange. The abnormal returns which are calculated using the market adjusted model, between t5 and t+15 days event windows are used to test this effect. In the regression, a dividend per share is regressed on the abnormal returns in the event windows from t-5 to t+15 days. The study uses data of 330 events for 88 companies from 2003 to 2007. The main findings of the study are; first, there is a significant negative relationship between cash dividends and abnormal returns after the announcement. The announcement of a higher cash dividend per share results in significant a higher negative abnormal return and the announcement of a lower cash dividend per share results in significant a lower negative abnormal return. In the case of only cash dividends announcements, the announcement of a cash dividend itself has a significant effect on share prices. In the event study analysis, only the announcement of cash dividends decrease results in a significant abnormal positive return in the event windows after the announcement day. Second, the adjustment of prices to new information starts on the announcement day and it continues at least 15 days. The most significant price adjustment takes place in the first three days. Third, there is no significant relationship between cash dividends and abnormal returns prior to the announcement day which implies that there is no significant information leakage prior to the information becoming publicly available. The observed negative relationship between cash dividends and abnormal share returns after the announcement on the Istanbul Stock Exchange can be explained by the tax clientele effect. In Turkey capital gains are taxed at lower than the dividend yields. Shareholders therefore prefer earnings to be retained rather than paid out as a dividend. Since the results document that there is no information leakage prior to the announcement day, the regulation and supervision of the capital markets in Turkey can be said to be effective and efficient in preventing insider trading in relation to cash dividends.
www.econstor.eu Macroeconomic Effects of Financial Uncertainty

This paper investigates the macroeconomic effects of uncertainty originating in the financial sector. My contribution is twofold. First, I document empirical relevenace of financial uncertainty using SVAR methods. Then, I employ the DSGE framework developed by Gertler and Karadi (2011) to uncover the underlying transmission mechanism. The model generates macroeconomic dynamics that are consistent with the SVAR evidence. In particular, an increase in financial uncertainty raises the risk premium and leads to a decline in output, consumption, investment and hours worked. This outcome arises mainly because of an endogenous tightening of the financial constraint, which in turn triggers the financial accelerator mechanism. Finally, internal habit formation and nominal rigidities act as additional amplification mechanisms for financial uncertainty shocks.
Joint Optimization of Energy Conservation and Migration Cost for Complex Systems in Edge Computing

By means of the complex systems, multiple renewable energy sources are integrated to provide energy supply for users. Considering that there are massive services needed to process in complex systems, the mobile services are offloaded from mobile devices to edge servers for efficient implementation. In spite of the benefits of complex systems and edge servers, massive resource requirements for implementing the increasing resource requests decrease the execution efficiency and affect the whole resource usage of edge servers. Therefore, it remains an issue to achieve dynamic scheduling of the computing resources across edge servers. With the consideration of this issue, a Balanced Resource Scheduling Method, named BRSM, for trade-offs between virtual machine (VM) migration cost and energy consumption of VM migrations for edge server management, named BRSM, is designed in this paper. Technically, we analyze the load conditions of edge servers and formulate the energy consumption of VM migrations and VM migration cost as a multi-objective optimization problem. Then, we propose a dynamic resource scheduling method for WMAN to deal with the multi-objective optimization problem. In addition, nondominated sorting genetic algorithm III (NSGA-III) is adopted to generate optimal resource scheduling strategies. Finally, we conduct experiment simulations to testify the efficiency of the proposed method BRSM.
Bolt Looseness Identification using Faster R-CNN and Grid Mask Augmentation

The quality of bolted connections is important for modular steel construction. This paper presents an automated looseness detection of bolted joints using faster region-convolutional neural networks (Faster R-CNN) with grid mask augmentation. Faster R-CNN has an ability to accurately detect an object and identify the object class. Our application leverages this ability for distinguishing the looseness levels into visually tight, loose, and unidentified bolted connections. Grid mask and flipping augmentation is used for the model to be more accurate with small dataset of bolted joints. Faster R-CNN with ResNeXt-101 backbone with grid mask augmentation shows promising mean average precision of detecting joints which is increased by 9.6% from without augmentation. Compared with YOLOF, our Faster R-CNN with ResNeXt-101 backbone has higher mAP by 0.94% and the integrated system with cloud computing allows our system to practically work real time.
Survey of Quadruped Robots Coping Strategies in Complex Situations

As an important branch of mobile robots, quadruped robots have high flexibility, high adaptability, and high dynamics, which provide excellent maneuverability and environmental adaptability. In the past ten years, researchers have done a lot of research on the ability of the quadruped robot to cope with the complex environment and published many results in order to make the working environment of the quadruped robot closer to reality. This paper collected these research results and divided these literatures into three categories according to different situations: crossing challenging terrain, walking on slope, and coping with interference, respectively, introducing representative methods. The purpose of this review is to summarize and analyze the previous research results and provide guidance for future research on quadruped robots in complex situations.
The effectiveness and cost-effectiveness of the Incredible Years® Teacher Classroom Management programme in primary school children: results of the STARS cluster randomised controlled trial

Background. We evaluated the effectiveness and cost-effectiveness of the Incredible Years® Teacher Classroom Management (TCM) programme as a universal intervention, given schools ’ important influence on child mental health. Methods. A two-arm, pragmatic, parallel group, superiority, cluster randomised controlled trial recruited three cohorts of schools (clusters) between 2012 and 2014, randomising them to TCM (intervention) or Teaching As Usual (TAU-control). TCM was delivered to teachers in six whole-day sessions, spread over 6 months. Schools and teachers were not masked to allocation. The primary outcome was teacher-reported Strengths and Difficulties Questionnaire (SDQ) Total Difficulties score. Random effects linear regression and marginal logistic regression models using Generalised Estimating Equations were used to analyse the outcomes. Trial registration: ISRCTN84130388. Results. Eighty schools (2075 children) were enrolled; 40 (1037 children) to TCM and 40 (1038 children) to TAU. Outcome data were collected at 9, 18, and 30-months for 96, 89, and 85% of children, respectively. The intervention reduced the SDQ-Total Difficulties score at 9 months (mean ( S . D .):5.5 (5.4) in TCM v. 6.2 (6.2) in TAU; adjusted mean difference = − 1.0; 95% CI − 1.9 to − 0.1; p = 0.03) but this did not persist at 18 or 30 months. Cost-effect-iveness analysis suggested that TCM may be cost-effective compared with TAU at 30-months, but this result was associated with uncertainty so no firm conclusions can be drawn. A priori subgroup analyses suggested TCM is more effective for children with poor mental health. Conclusions. TCM provided a small, short-term improvement to children ’ s mental health particularly for children who are already struggling. the study children during the study follow-up. Schools access to other training and support services not The effectiveness and cost-effectiveness of the Incredible YearsA (R) Teacher Classroom Management programme in primary school children: results of the STARS cluster randomised controlled trial
Global Asset Allocation Strategy Using a Hidden Markov Model

This study uses the hidden Markov model (HMM) to identify the phases of individual assets and proposes an investment strategy using price trends effectively. We conducted empirical analysis for 15 years from January 2004 to December 2018 on universes of global assets divided into 10 classes and the more detailed 22 classes. Both universes have been shown to have superior performance in strategy using HMM in common. By examining the change in the weight of the portfolio, the weight change between the asset classes occurs dynamically. This shows that HMM increases the weight of stocks when stock price rises and increases the weight of bonds when stock price falls. As a result of analyzing the performance, it was shown that the HMM effectively reflects the asset selection effect in Jensen’s alpha, Fama’s Net Selectivity and Treynor-Mazuy model. In addition, the strategy of the HMM has positive gamma value even in the Treynor-Mazuy model. Ultimately, HMM is expected to enable stable management compared to existing momentum strategies by having asset selection effect and market forecasting ability.
X-Ray Dating of Ancient Linen Fabrics

We propose a new method for dating ancient linen threads by inspecting their structural degradation by means of wide-angle X-ray scattering. X-ray dating of a textile sample can be performed nondestructively and on a submillimeter area, e.g., 0.2 0.5 mm2, exploiting new table-top X-ray micro-sources. A theoretical formula is derived for dating linen samples directly from wide-angle X-ray scattering measurements. Our preliminary results show that X-ray dating results are in agreement with other dating sources, such as the radiocarbon method and historical records, if some conditions are satisfied. Indeed, this new dating method can be applied only to threads not older than about thirty centuries because of the saturation of the structural degradation with age. Moreover, the method can be applied only on textiles in which cellulose degradation is mainly due by natural aging arising from thermal, hydrolytic, photolytic, photochemical, and oxidative processes. Analyses can be repeated several times on the same sample, which remains unaltered for other complementary characterization procedures. The proposed X-ray dating of some ancient linen fabrics opens the way to explore limits and potentialities of this new approach and to further develop a new dating method, alternative to the existing ones for specific applications in archeological studies.