Miracle-dz/UniFAR-FTUs huggingface dataset:
PROCEEDINGS OF THE 12 th WORLD RABBIT CONGRESS

The caecum has a major role in rabbits’ development, is the site where microbial digestion of carbohydrates and proteins occurs and yet it is characterized by an abundant colonization of bacterial flora. Volatile fatty acids (VFA) are end products of fermentation in the caecum of rabbits, which provides as an important source of energy. This study aimed to evaluate the production of volatile fatty acids of growing rabbits fed different levels of inclusion of beet pulp (0, 9.41, 18.85, 32.94, 42.67 g/kg). Samples of the caecum content of 12 slaughtered rabbits randomly selected from each group were collected. The caecum content was secured in falcon tubes with the subsequent addition of 1ml of metaphosphoric acid solution 25% and frozen in freezer at -18ºC. The samples were transferred to centrifuge tubes and were homogenized for 10 minutes at 3000rpm in a refrigerated centrifuge, the supernatants were collected and filtered into millipore filters of 0.45 µm and the aliquots were then analyzed for acetic, propionic and butyric acids through the gas chromatograph CG Shimadzu 17A. The results were statistically analyzed through unidirectional ANOVA, with beet pulp levels as the main factor. For all data, linear and quadratic effects were studied for the inclusion levels of beet pulp using a polynomial contrast. There was no statistical difference between the groups for acetic (P>0.001) and butyric acids (P>0.001). For propionic acid, a linear increase (10.51 to 17.63 µ g/ml, P<0.001) was observed as the inclusion of beet pulp in the diet of growing rabbits increases. It is observed that the inclusion of beet pulp in the diet of growing rabbits exerts a beneficent effect on animal cecum, improving the development of the microbiota, resulting in a greater fermentation of substrates and greater production of volatile fatty acids in growing rabbits.
The Effects of PNF Stretching on Range of Motion, Strength, Balance and Postural Adaptations in Older Women with Osteoarthritis

Approximately 30% of the elderly population (> 65 years) experience frequent falls which negatively impacts their physical well-being. This problem is even more pronounced in elderly women who exhibit chronic conditions such as osteoarthritis. As a result, there is a continuous need for non-invasive programs aimed at the improvement of balance, flexibility and strength. The purpose of this research was to examine if proprioceptive neuromuscular facilitated (PNF) stretching exercises enhanced flexibility, sstrength, static balance, and postural adaptations in three elderly women with osteoarthritis in their lower extremities. Three females (M = 64.3, SD = 3.85) completed a pre-test, 12 stretching sessions (3 per week for four weeks), a post-test, and a retention test. Static balance in standing was measured on a force place and was inferred from center of pressure (COP) path length (cm) whereas COP sway area (cm2) was used to examine changes in postural adaptations. The flexibility was inferred from range of motion of the hip, knee, and ankle joints measured with a goniometer, whereas a sit to stand test was used to capture the changes in strength. Descriptive results showed that all three participants experienced an increase in strength, but even more importantly clinically relevant changes in ROM were evident in the majority of the muscle groups targeted. Static balance remained unaffected, but as expected, the ability to generate dynamic postural adaptations was enhanced, which may have an important impact on overall prevention of falling and staggering. Although the sample size was small, the findings appear to be robust across the participants thus confirming the usefulness of PNF stretching on different aspects of gross motor function in women with osteoarthritis. Sports Injuries & Medicine Przysucha E and Klarner T. Sports Injr Med: 5: 173. www.doi. org/10.29011/2576-9596.100073 www.gavinpublishers. com
Cytoplasmic and Nuclear HER 4 Expression in HER 2 Negative Breast Cancer Cell Lines (

HER4 cleavage and its subcellular localisations have been previously proven to mediate anti-HER2 resistance. The description of the HER4 subcellular localisations in HER2 negative breast cancer, on the other hand, is incomplete. The objective of this study was to determine the cytoplasmic and nuclear expression of HER4 in HER2 negative breast cancer cell lines in order to gain a better understanding of the key features of HER4 signalling in the context of antiHER2 resistance. MCF-7 and MDA-MB-231 cells were cultured for 48 h at 37 °C and 5% CO2 in fresh DMEM medium with 10% foetal bovine serum and 1% penicillin-streptomycin. The western blot analysis for HER4 protein was done on cytoplasmic and nuclear extracts that had been obtained previously using the NE-PER Nuclear and Cytoplasmic Extraction Kit. Cytoplasmic and nuclear HER4 proteins were expressed in a variety of sizes, including 120 kDa, 55 kDa, 50 kDa, and 43 kDa. MCF-7 cells expressed significantly more cytoplasmic HER4120kDa than MDA-MB-231 cells. MCF-7 exhibited a single nuclear HER4 variant with a molecular weight of 50 kDa, whereas MDA-MB-231 expressed two nuclear HER4 variants with molecular weights of 50 kDa and 43 kDa. In comparison to MDA-MB-231 cells, MCF7 cells exhibit higher level of cytoplasmic HER4120kDa with positive nuclear HER450kDa expression. Due to the presence of ER and PR in MCF-7, it is important to investigate if the interaction of these HER4 variants with ER and PR confers resistance to anti-HER2 treatment on breast cancer. Meanwhile, results from MDA-MB-231 cells indicate that nuclear HER4 contributes to the development of TNBC.
Inverse-Consistent Deep Networks for Unsupervised Deformable Registration of Brain MR Images

—Deformable registration is a fundamental task in brain image analysis, aiming to establish a dense and non-linear correspondence between a pair of images. Conventional unsupervised networks usually ignore the inverse-consistent property (essential for diffeomorphic mapping) of transformations between a pair of images. Also, a smoothness constraint is generally used to encourage the to-be-estimated transformation to be locally smooth, which could not completely avoid folding. To this end, we propose an I nverse-C onsistent deep Net work ( ICNet ) for unsupervised deformable registration of brain magnetic resonance imaging (MRI) scans. Speciﬁcally, we develop an inverse-consistent constraint to encourage that a pair of images are symmetrically deformed toward one another. Besides the smoothness constraint, we also employ an anti-folding constraint to further avoid folding in the transformation. Our method does not require supervision information, while encouraging the diffeomorphic property of the transformation. We evaluate our method on T1-weighted brain MRI for tissue segmentation and anatomical landmark detection, with results demonstrating the superior performance of our ICNet over several state-of-the-art approaches. Our code has been made publicly available.
Bone-Edge-Guided Generative Adversarial Network for Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs

—Dual-energy subtraction (DES) soft-tissue images can improve the detection performance for lung diseases and ﬁndings, but requiring specialized equipment to obtaining dual-energy X-ray exposures. Recent studies focus on bone suppression of chest X-rays (CXRs) using machine/deep learning techniques to enhance soft-tissue structures. However, most of the previous work produce the bone suppressed images with the style different from real DES soft-tissue images which clinical values have been conﬁrmed. Also, existing bone suppression methods based on deep learning generally ignore the anatomical structure information (e.g., edges of ribs and clavicles) in CXRs. In this work, we propose a bone Edge-guided Generative Adversarial Network (EGAN) to generate DES-like soft-tissue images from standard CXRs, which can automatically and quickly detect the borders of rib and clavicle in CXRs and explicitly employ the anatomical structure information of bones in CXRs. Speciﬁcally, in EGAN, we ﬁrst design a deep network for bone edge detection, and train this detector based on 73 CXRs with manual delineations to generate the rib-and-clavicle edge map of each input CXR automatically. With the concatenation of an original CXR and its corresponding edge map as input, we further develop a GAN model to generate a DES residual image and a soft-tissue image. Experiments are performed on 504 subjects (each equipped with a CXR and a DES soft-tissue image), and the results demonstrate that the proposd EGAN can produce DES-like soft-tissue images with high-quality. We also apply the trained EGAN model to four public datasets with CXRs obtained by different types of X-ray machines. The results show that our method can produce visually attractive DES-like soft-tissue images, and these images can be used for reliable diagnosis of tuberculosis.
THE TRIUMPH OF COHORT-EFFECTS IN THE EXPLANATION OF MORTALITY CHANGE: A NEW AGE-PERIOD-COHORT ANALYSIS OF ADULT CAUSE- SPECIFIC MORTALITY IN THE UNITED STATES*

This study examined the temporal changes in U.S. adult mortality by cause of death and sex over a 40-year period in the second half of the 20 century. It applied the Intrinsic Estimator to log-linear APC models to simultaneously account for age, period, and cohort variations in mortality rates for four leading degenerative causes of deaths – heart disease, stroke, lung cancer, and female breast cancer. The results show that the large mortality reductions since the late-1960s continued well into late-1990s and these reductions were predominately contributed by cohort effects. Cohort effects are found to differ by specific causes of death examined, but they generally show substantial survival improvements, especially for cohorts born since 1900. Implications of these results are discussed with regard to epidemiological transition theory, the theory of technophysio evoluation, differential cohort accumulation of health capital and life time exposures to socioeconomic and behavioral risk factors, and period changes in diagnostic techniques and medical treatment.
SARS-CoV-2 hyperimmune globulin for severely immunocompromised patients with COVID-19: a randomised, controlled, double-blind, phase 3 trial

Background: Severely immunocompromised patients are at risk for severe COVID-19. Benefit from convalescent plasma in these patients is suggested but data from randomised trials are lacking. The aim of this study is to determine efficacy of SARS-CoV-2 hyperimmune globulin (COVIG) in treatment of severely immunocompromised, hospitalised COVID-19 patients. Methods: In this randomised, controlled, double-blind, multicentre, phase 3 trial, severely immunocompromised patients who were hospitalised with symptomatic COVID-19 were randomly assigned (1:1) to receive 15 grams of COVIG or 15 grams of intravenous immunoglobulin without SARS-CoV-2 antibodies (IVIG, control). Patients included were solid organ transplant patients with three drugs from different immunosuppressive classes or patient with disease or treatment severely affecting B-cell function. Patients that required mechanical ventilation or high flow nasal oxygen were excluded. All investigators, research staff, and participants were masked to group allocation. The primary endpoint was occurrence of severe COVID-19 evaluated up until day 28 after treatment, defined as the need for mechanical ventilation, high-flow nasal oxygen, readmission for COVID-19 after hospital discharge or lack of clinical improvement on day seven or later. This trial is registered with Netherlands Trial Register (NL9436). Findings: From April, 2021, to July, 2021, 18 participants were enrolled at three sites in the Netherlands; 18 patients were analysed. Recruitment was halted prematurely when casirivimab/imdevimab became the recommended therapy in the Dutch COVID-19 treatment guideline for seronegative, hospitalised COVID-19 patients. Median age was 58 years and all but two were negative for SARS-CoV-2 spike IgG at baseline. Severe COVID-19 was observed in two out of ten (20%) patients treated with COVIG compared to seven of eight (88%) in the IVIG control group (p = 0.015, Fisher's exact test). Interpretation: COVIG reduced the incidence of severe COVID-19 in severely immunocompromised patients, hospitalised with COVID-19. COVIG may be a valuable treatment in this patient group and can be used when no monoclonal antibody therapies are available. Funding: The Netherlands Organisation for Health Research and Development, Sanquin Blood Supply Foundation.
1 . 4 μ m Pixel , 8 MP , > 5 μ m epi , RGB-IR Image Sensor

Image sensors with 1.4 μm pixel size, 8 MP array, stacked BSI, 65 nm technology, have been fabricated with thick (>5 μm) epi silicon as a basic pre-requisite condition for increased near-infrared (NIR) response. Two backside surface processing variants were prepared and patterned with RGB-IR color filter array: one with NIR-enhancement inverted pyramids, and a baseline without NIR-enhancement features. An analysis is provided on the performance of these structural variants for RGB-IR imaging. Application specific recommendations are made for the pixel variants developed.
The Immediate Mental Health Effects of the 2020 Artsakh War on Armenians: A Cross-Sectional Study

Background: While previous studies show the long-term and transgenerational effects of war on mental health, immediate effects on mental health are relatively understudied. The 44-day 2020 Artsakh War (September 27-November 10, 2020) resulted in an estimated 5,000 Armenian casualties, displacement of half the Artsakh population, and ongoing captivity of Armenian prisoners of war. This is the first study post-war to quantify depression, anxiety, and post-traumatic stress disorder (PTSD) levels among the Armenian population. Methods: We conducted a cross-sectional study from February 3-May 31, 2021. Using Google Forms, we implemented a 75-item survey, including depression (PHQ-9), anxiety (GAD-7), and PTSD (PCL-5) questionnaires. We used six binary (yes/no) questions to define direct-exposure (DE) and no direct exposure (NDE) groups. We used independent samples t-tests to compare mean scores between groups. Results: There were 825 participants from 32 countries, 48% from the United States and 33% from Armenia and Artsakh. All participants from Artsakh (100%), 89.2% from Armenia, and 46.6% from the United States were directly exposed to the war. The DE (n=529) group exhibited significantly higher PHQ-9 (p=0.0001), GAD-7 (p=<0.0001), and PCL-5 (p=0.0001) mean scores, than the NDE (n=296) group. Those who sustained a physical injury (n=20) had the highest average clinically relevant PTSD score (mean=39.5, SD=24). Conclusion: Our results suggest an association between direct exposure to war in Artsakh and increased depression, anxiety, and PTSD severity, suggesting an immediate need for mental health resources. Those who lost a loved one, had a loved one get injured, and had a loved one participate in the 2020 Artsakh War had higher PHQ-9, GAD-7, and PCL-5 mean scores relative to those who did not. Implications of this study include the development of targeted evidence-based psychotherapeutic methods based on specific direct exposure factors.
THD analysis and cost comparison for an N-level H-bridge inverter incorporating passive and active filters

Multilevel H-bridge inverters have grown in popularity in electronic direct current (DC) to alternating current (AC) power conversion. In the renewable energy field, H-bridge inverters are used for converting DC voltage obtained from solar panels to AC voltage. However, H-bridge inverters produce undesirable odd harmonics in their output. Several Hbridges are, therefore, usually cascaded to reduce the total harmonic distortion (THD) in their output, but the results aren’t satisfactory in most cases. In this paper, both active and passive filters are incorporated in a cascaded H-bridge inverter to reduce the THD further. Then cost comparison is made of cascaded H-bridge inverters (3, 5, 7, 9, and 11levels) without a filter and multilevel cascaded H-bridge inverters (3, 5, 7, 9, and 11-levels) with a passive filter or active filter. Powersim (PSIM) platform is used to perform the THD analysis.
Aging Medicine and Healthcare

Background/Purpose: Poor sleep quality increases with age, contributing to many problems such as falling, poor social functioning, and low quality of life. Our study aimed to evaluate the prevalence and associated factors of poor sleep quality among older Vietnamese adults. Methods: In this cross-sectional study, we conducted face-to-face interviews among community-dwelling older people living in District Eight in Ho Chi Minh City. We used the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality. A total score ≥ 5 indicated poor sleep quality. Fried’s criteria were used to identify frailty, and comorbid diseases were based on medical records. Results: The data of 592 participants were collected (mean age 71.2±7.7, 67.4% female). The prevalence of poor sleep quality was 55.9%, with a mean PSQI score of 7.26±4.51. Factors independently associated with poor sleep quality including age (odds ratio [OR]=1.03, 95% confidence interval [CI]= 1.01–1.06 , p =0.047), low educational attainment (OR=1.98, 95% CI: 1.33– 2.93, p =0.001)
Pontos de transição: a escalada rumo à maturidade de Sistemas de Gestão da Qualidade

The demand for measurement and evolution methods of Quality Management System (QMS) Maturity has grown due to the great number of companies certified at ISO 9001. This paper aimed to identify the constructs and key transition points in the Maturity of QMSs through an empirical research using factorial and cluster analyses. Data was collected from a sample composed of 179 Brazilian companies of several sizes, segments and geographical positions. In addition to the constructs found in the literature, the empirical results identified a new construct - “Agility and Integration by Information Technology”. Although QMSs are widespread in industry, the identification of constructs and their transition points by cluster analysis can be useful to managers and researchers interested in the maturity management process. This study can be especially useful to guide the efforts of experts, consultants and managers in increasing company operational performance.
The Analysis of Virtual Assembly Technology

The paper introduces the basic connect of virtual products design and the theory, the process, the methods of virtual assembly technology. The authors design turbine blade by the virtual assembly technology, analysis and check the spare parts design and structure design. According to the results, the spare parts design and structure design are corrected. So the design, analysis and check process of new product developing can be made by computer in virtual environment.
Implementing the European Quality Assurance in Vocational Education and Training (EQAVET) at National Level: Some Insights from the PEN Leonardo Project

EQAVET, the quality assurance tool in vocational and educational training, was developed in response to the need for a supply of a trained workforce for labour market needs. Implementation of EQAVET at national level, however, remains a challenge. The research reported here focused on the implementation of QA processes by VET providers in 4 countries: Malta, Italy, Turkey, and Sweden. Data was collected through a questionnaire with 62 VET providers. Responses showed that there is an overall commitment to quality. There is, however, little knowledge of EQAVET across the countries, with the exception of Malta. None the less, all VET providers have implemented some aspects of EQAVET, even if not always intentionally. The situation is, however, far from EQAVET being fully implemented. Reflections are made on whether the EQAVET model specifically or qualification assurance principles assurances should be promoted across Europe.
Evidence of Magnetic Reconnection with Multiple X Lines and Flux Ropes in Thin Magnetotail Currents Observed by the MMS Spacecraft: Results of Grad–Shafranov Reconstruction

There is some observational evidence for the existence of multiple X line magnetic reconnection (MR) in various planetary magnetotails but the overall observationally based MR topology in two or three dimensions is still not available. This study reports the first 2D structures of MR with multiple X lines and magnetic islands observed by the Magnetospheric Multiscale (MMS) spacecraft in the Earth’s magnetotail based on the Grad–Shafranov (GS) reconstruction model with temperature anisotropy. The tearing mode geometry is revealed within the spatial domain of 3800 km × 800 km with multiple X lines and magnetic islands on the spatial scale of the sub-ion inertial length or a few times the electron gyroradius. The MR event is seen by all four MMS spacecraft but the magnetic islands are caught only by the MMS3 spacecraft, and exhibit large firehose-type temperature anisotropy. The GS reconstructed maps based on the MMS1, 2, and 4 show a single X line and partial ion-scale magnetic islands with a smaller degree of temperature anisotropy. The reconstruction results remain the same for various energy closures, and the firehose-type anisotropy is found to yield smaller magnetic islands than the isotropic cases, which is opposite to the previous findings for MR events with mirror-type temperature anisotropy.
WSN-BASED SMART SENSORS AND ACTUATOR FOR POWER MANAGEMENT IN INTELLIGENT BUILDINGS

: Wireless sensing network (WSNs) have the ability to monitor as well as control the situational information for various intelligent service so day by day the demand for wireless sensor networks(WSNs) goes on increasing. The consumption of energy in residential buildings is increasing day by day due to increase in urban population and increase in usage of AC appliances. Energy generated is not sufficient to meet energy demand. Therefore there is a need to save energy. The use of smart energy management system can assist in reducing the energy usage in an efficient way. Intelligent Power Management is the combination of smart sensors and actuators. The design and development of an intelligent monitoring and controlling system for home appliances in a real time system is presented in this project. This system principally monitors the electrical parameters such as voltage and current and subsequently calculates the power consumption of the home appliances that are need to be monitored. The innovation of this system is controlling mechanism implementation in Iot based by server. The user can control the home appliances by mobile app using server data. The developed system is a low-cost and ﬂexible in operation and thus can save electricity expense of the consumers. Also the proposed system is an economical and easily operable. Due to these intelligent characteristics it becomes an electricity expense reducer and people friendly. Adopting WSNs for power management provides great advantages over traditional wired system. By using WSN technology data can be collected through sensing unit and transferred wirelessly to a control system for operation and management
The Development of total software NC system for Laser-cutting machine

It analyzes the task of total software NC system for laser cutting machine according to the control demand for high speed laser cutting,and introduces the mechanism of multi-task real-time operation and data transformation in the Windows platform,and also expounds the handling mechanism in the cutting process for some key functions,such as go back and fault recovery and so on.By using this system in the practical machine tool,the system can well satisfy the control demand for the high speed metal sheet cutting.