Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Gender on Growth Traits of Broiler Rabbits

The present study deals with the comparison of the impact of gender on selected production parameters of rabbits in conditions of intensive farming. The aim of this work was to study and to process the professional and scientific literature that deals with the growth of broiler rabbits. Another objective was to evaluate the growth parameters of the analyzed broiler rabbits population. Followed by an analytical evaluation of live weight differences between male and female hybrid subjects, and a confrontation of observed results with those published in professional and scientific publications. In particular time periods we compared the values of live weight of both sexes. At the 35 days of age live weight of both sexes were almost balanced, but in the 56th day we observed a slight difference in the values of live weight between the sexes. In the last time period, from the 77th to 105th day, the offspring of both sexes reached higher live weight, while we once again identified just small differences in the values of body weight between the two sexes. Over the whole period, we found a slightly higher live weight of males, but the differences between these values are minimal. This means, there is no statistically significant difference between males and females. In terms of statistical significance, we therefore found that the both sexes are growing equally, thus guiding the sex of newborn offspring, is in principle ineffective.
THE LAND COVER CLASSIFICATION USING A FEATURE PYRAMID NETWORKS ARCHITECTURE FROM SATELLITE IMAGERY

Abstract. Extracting land cover information from satellite imagery is of great importance for the task of automated monitoring in various remote sensing applications. Deep convolutional neural networks make this task more feasible, but they are limited by the small dataset of annotated images. In this paper, we present a fully convolutional networks architecture, FPN-VGG, that combines Feature Pyramid Networks and VGG. In order to accomplish the task of land cover classification, we create a land cover dataset of pixel-wise annotated images, and employ a transfer learning step and the variant dice loss function to promote the performance of FPN-VGG. The results indicate that FPN-VGG shows more competence for land cover classification comparing with other state-of-the-art fully convolutional networks. The transfer learning and dice loss function are beneficial to improve the performance of on the small and unbalanced dataset. Our best model on the dataset gets an overall accuracy of 82.9%, an average F1 score of 66.0% and an average IoU of 52.7%.
First constraints on small-scale non-Gaussianity from UV galaxy luminosity functions

UV luminosity functions provide a wealth of information on the physics of galaxy formation in the early Universe. Given that this probe indirectly tracks the evolution of the mass function of dark matter halos, it has the potential to constrain alternative theories of structure formation. One of such scenarios is the existence of primordial non-Gaussianity at scales beyond those probed by observations of the Cosmic Microwave Background. Through its impact on the halo mass function, such small-scale non-Gaussianity would alter the abundance of galaxies at high redshifts. In this work we present an application of UV luminosity functions as measured by the Hubble Space Telescope to constrain the non-Gaussianity parameter fNL for wavenumbers above a cut-off scale kcut. After marginalizing over the unknown astrophysical parameters and accounting for potential systematic errors, we arrive at a 2σ bound of fNL=71+426−237 for a cut-off scale kcut=0.1 Mpc−1 in the bispectrum of the primordial gravitational potential. Moreover, we perform forecasts for the James Webb Space Telescope and the Nancy Grace Roman Space Telescope, finding an expected improvement of a factor 3–4 upon the current bound.
Influence of the density pole on the performances of its gamma-kernel estimator

In this paper, we aim at highlighting the in uence of the density pole on the performances of its gamma-kernel estimator. To do this, we performed a comparative study for the performances of the gamma-kernel estimators with those provided by other bias effect correction techniques at the bounds, using the simulation technique. In conclusion, the results obtained conrm those provided in the literature and show that in some cases the normalization of the gamma estimators can considerably improve local and global performances of the gamma-kernel estimators.
Single-crystal perovskite detectors: development and perspectives

Visible-light and X-ray detectors based on semiconductors as light absorption and charge transport materials are widely used in image sensing, optical communication, biological detection, inspection, etc. Metal halide perovskite materials are promising candidates for visible-light and X-ray detectors due to their long carrier diffusion length, low trap density, strong absorption and tunable bandgap. Compared with the widely investigated polycrystalline thin films, single crystals exhibit better optoelectronic properties, showing potential for higher-performance detector devices. In this review, we will summarize the recent development of visible-light and X-ray detectors based on perovskite single crystals with different morphologies and device structures. The strategies to optimize the material properties and device performance will be discussed in detail. Finally, challenges and perspectives are proposed to promote further improvement in performance and practical application of single-crystal perovskite detectors.
Presence of salmonella spp., listeria monocytogenes, escherichia coli O157 and nitrate-nitrite residue levels in Turkish traditional fermented meat products (soudjouck and pastrami)

#nofulltext# --- Şakar, Fitnat Şule (Arel Author), Buyukunal, Serkan Kemal (Arel Author), Erginbas, Cinar (Arel Author) --- Conference: II International VETistanbul Group Congress. DIGEST : Saint-Petersburg, Russia, 07-09 April 2015
Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing

This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a means for collecting human kinetic and kinematic data at the foot-ankle complex and at the wrist are reviewed. Lessons learned from past experiments are addressed, as well as what comprises the current SSTK based on what the researchers learned over the course of multiple studies. Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution.
Utilization of Oil Properties to Develop a Spreading Rate Regression Model for Nigerian Crude Oil

The target of this study is to develop a spreading rate regression model capable of predicting rate of spread of Nigerian crude oil spills on water. The major factors responsible for spreading rate of crude oil on water were considered, namely surface tension, viscosity, and specific gravity/American Petroleum Institute degree (0API), all at specified temperature values. The surface tension, viscosity and density parameters were interactively measured under controlled factorial analysis. The spreading rate of each crude oil was determined by artificially spilling them on laboratory calm/stagnant water in a rectangular tank and their averages were also computed. These averages were used to develop a regression model equation for spreading rate. The model developed indicated that an average spreading rate was 3.3528 cm/s at 37.5°C and the predictive regression model is evaluated with the interactions of specific gravity, viscosity and surface tension. It is convenient to state that the model will predict the spread rate of crude oils which possess imputed physicochemical properties having pour point averaged 15.5°C on calm seawater.
NBER WORKING PAPER SERIES HETEROGENEOUS EFFECTS OF HEALTH INSURANCE ON BIRTH RELATED OUTCOMES: UNPACKING COMPOSITIONAL VS. DIRECT CHANGES

When women of childbearing age gain health insurance, we expect their birth outcomes to improve, but comparing births that occur before and after policy changes may confound two separate impacts of coverage. For one, health insurance could affect who gives birth, through reduced costs of contraception. Health insurance could also directly improve maternal and child health among those who give birth, through additional prenatal resources. We address this question using the Affordable Care Act young adult provision, comparing birth related outcomes for those aged 24-25 years after the law, to outcomes among older young adults. We show that since the law subsidized contraceptives mainly among higher socioeconomic groups, the composition of mothers shifted towards less advantaged groups. Accounting for this shift, we find evidence of direct improvements in prenatal care and pregnancy-related health (reduced gestational diabetes and hypertension). Jie Ma Xi'an Jiaotong University 28 West Xianning Street Xi'an, Shaa 710000 China jie_ma@xjtu.edu. cn Kosali I. Simon O’Neill School of Public and Environmental Affairs Indiana University 1315 East Tenth Street Bloomington, IN 47405-1701 and NBER simonkos@indiana.edu
Global Scheduling Real-Time Parallel Tasks on Multicore Platforms

Traditional real-time task scheduling strategies only considers cores scheduling, and do not take in account memory access and cache effects on multicore platforms. In this paper, we propose real-time parallel scheduling (PRTTS) strategy on multicore platforms. Each task is represented as a directed acyclic graph (DAG). The priorities of tasks are assigned according to task periods (rate monotonic, RM). In PRTTS scheduling strategy, priorities of tasks that access memory are promoted over priorities of tasks not accessing memory. Tasks accessing the data in the cache is dynamically raised to highest priority. The results of simulation experiment show that proposed new scheduling strategy offers better performance in terms of core utilization and schedulability rate of tasks.
Neurofilament Light Chain Related to Longitudinal Decline in Frontotemporal Lobar Degeneration.

Objective Accurate diagnosis and prognosis of frontotemporal lobar degeneration (FTLD) during life is an urgent concern in the context of emerging disease-modifying treatment trials. Few CSF markers have been validated longitudinally in patients with known pathology, and we hypothesized that CSF neurofilament light chain (NfL) would be associated with longitudinal cognitive decline in patients with known FTLD-TAR DNA binding protein ~43kD (TDP) pathology. Methods This case-control study evaluated CSF NfL, total tau, phosphorylated tau, and β-amyloid1-42 in patients with known FTLD-tau or FTLD-TDP pathology (n = 50) and healthy controls (n = 65) and an extended cohort of clinically diagnosed patients with likely FTLD-tau or FTLD-TDP (n = 148). Regression analyses related CSF analytes to longitudinal cognitive decline (follow-up ∼1 year), controlling for demographic variables and core AD CSF analytes. Results In FTLD-TDP with known pathology, CSF NfL is significantly elevated compared with controls and significantly associated with longitudinal decline on specific executive and language measures, after controlling for age, disease duration, and core AD CSF analytes. Similar findings are found in the extended cohort, also including clinically identified likely FTLD-TDP. Although CSF NfL is elevated in FTLD-tau compared with controls, the association between NfL and longitudinal cognitive decline is limited to executive measures. Conclusion CSF NfL is associated with longitudinal clinical decline in relevant cognitive domains in patients with FTLD-TDP after controlling for demographic factors and core AD CSF analytes and may also be related to longitudinal decline in executive functioning in FTLD-tau.
Current regulations will not protect patient privacy in the age of machine learning

• Tools from machine learning are showing great promise in solving challenging problems in healthcare by leveraging their ability to parse and integrate massive datasets • Currently, this progress comes at the expense of privacy, since the current state of privacy legislation is not equipped to handle the novel challenges presented by widespread adoption of ML • Changing the current U.S. “reasonable expectation of privacy” doctrine and ending the restriction of HIPAA to only the healthcare industry are two specific steps local or federal governments can take to protect privacy in the age of ML
Stability of Fruit Quality Traits of Different Strawberry Varieties under Variable Environmental Conditions

Strawberry fruit quality traits can be affected by genotype–environment interactions, determining the final consumer acceptance of fruits. Trait stability under varying environments is necessary to ensure the fruit quality of strawberries selected by breeding programs. Hence, inter- and intra-annual variation of organoleptic and functional fruit quality parameters of five strawberry varieties throughout four consecutive cropping seasons was analyzed to assess their relative stability. In most varieties, organoleptic parameters showed higher inter-annual stability but greater variability throughout the season, while the reverse was true for the functional quality parameters. Relative humidity and mean and minimum temperatures partially accounted for fruit quality variation but other factors along with the genotype may also have an influence. Among the varieties, ‘Splendor’ displayed greater year-on-year stability in organoleptic parameters, and ‘Sabrina’ and Candonga® showed higher inter- and intra-annual stability on functional fruit quality, respectively. Environmental variation did not affect fruit quality parameters similarly in all strawberry varieties. In ‘Sabrina’ and Candonga® antioxidant capacity (TEAC) was greater and stable throughout the cropping season, underlining TEAC as a tool for varietal selection, and suggesting these two varieties as parents for breeding programs that seek healthy features and high-quality fruits that meet consumer demands.
Molecular Characteristics of a Carbapenemase-producing Enterobacter Species and Klebsiella Species Outbreak in a Japanese University Hospital

Carbapenemase-producing Enterobacteriaceae (CPE) have been reported worldwide, but the types of carbapenemase vary between countries. Metallo-betalactamase (MBL) IMP (blaIMP) is the most common type of carbapenemase in Japan. CPE outbreaks occurred in our hospital’s neonatal intensive care unit (NICU) between October 2014 and October 2015. The aim of this study was to evaluate the results of active surveillance and to establish more effective CPE detection methods. We also investigated the molecular epidemiological characteristics of CPE in Japan. During the outbreak period, active surveillance was performed on a weekly basis by analyzing fecal cultures from all patients admitted to the NICU. Between January 2014 and December 2015, which included the outbreak period described above, Enterobacteriaceae strains isolated by fecal culture or from clinical specimens were analyzed by antimicrobial susceptibility testing and double-disc synergy testing (DDST) using ceftazidime or imipenem with sodium mercaptoacetic acid, polymerase chain reaction (PCR), pulsedeld gel electrophoresis (PFGE), and conjugal transfer experiments. During the outbreak period we analyzed 1073 isolates detected by fecal culture from 285 patients. Of these, we detected 64 blaIMP-producing Enterobacteriaceae from 52 patients, all of whom were asymptomatic carriers (52/285, 18.2%). Klebsiella pneumoniae (33/64 strains, 51.6%) and Enterobacter cloacae (20/64 strains, 31.3%) were the predominant species. Of the 64 blaIMP-producing Enterobacteriaceae, 7 strains were susceptible to imipenem and meropenem. Active surveillance by fecal culturing and DDST of carbapenem-resistant and third-generation cephalosporin-resistant pathogens may be an effective strategy for identifying CPE carriers. Therefore, this strategy may contribute to infection control and prevent further spread of disease in healthcare settings.
The Diversity of TLR4-triggered Responses in Mouse Microglia

Microglia are the major immunocompetent effector cells of the CNS. Steadily monitoring their neighborhood they are always ready to transform to activated states upon encounters with danger-spelling signals provided by the sudden presence, abnormal concentration or an unusual molecular format of certain factors. Amongst a variety of receptors, microglia employ Toll-like receptors (TLRs) and their dual function for detecting exogenous as well as endogenous threats. TLR stimulation in microglia causes an innate immune reaction aiming at the protection of the CNS as well as promoting the repair of damaged tissue. Among the TLR family, TLR4 represents a specialized member because of its engagement with both of the major TLR signaling routes depending on the signaling adaptor molecules MyD88 and TRIF, respectively. This study aimed at deciphering the microglial response to bacterial LPS as the prototypic TLR4 agonist. We found microglia to differentially respond to structural variants of LPS as they come with different bacterial strains, thereby revealing a critical role for the co-receptor CD14. We could further show that microglial TLR(4) responses are organized in a complex fashion depending on the "strength" of the signal. Moreover, these responses are highly sensitive to modulation by secondary immune and non-immune signals. Finally, we demonstrated that microglial TLR(4) signaling undergoes reorganization during CNS maturation and acquires distinct functional profiles in different anatomical regions/populations. Together, these data argue for the versatility of the microglial TLR4 signaling, as being also subject to a high degree of regulation and (re)organization and as being instructed and required by the special conditions of the CNS.
Epigenetic editing using programmable zinc ginger proteins: inherited silencing of endogenous gene expression by targeted DNA methylation

Cancer development is not only the result of genetic mutations but also stems from modifications in the epigenetic code leading to an aberrant expression of genes relevant for cancer. The most studied epigenetic mark is DNA methylation of cytosines in the promoters of genes, which is associated with repressed gene expression. Hallmarks of cancer are aberrant silencing of tumor suppressor genes and the activation oncogenes by epigenetic means. We reasoned that the induction of targeted DNA methylation at endogenous loci will lead to the transcriptional repression of the target genes. Therefore, we used zinc finger based DNA-binding domains designed to target specifically an 18 bps DNA sequence. The DNA-binding domain was then fused to the catalytic active proportion of the DNA methyltransferase DNMT3A to induce targeted DNA methylation at the gene of interest. We show that targeted DNA methylation lead to silencing of gene expression of both, an oncogene and a tumor suppressor gene. Repression of a tumor suppressor gene lead to an increase of tumor cell growth; while silencing of the oncogenic transcription factor SOX2, lead to a decrease in cancer cell proliferation in vitro and to the inhibition of tumor growth in xenografts. The induced DNA methylation was maintained over cell generations and detectable up to 100 days post inoculation, which was associated with the repression of target gene expression and decreased expression of the proliferation marker Ki67. Overall our findings show that targeted DNA methylation can be used to specifically and stably silence gene expression.
Multiview feature fusion optimization method for image retrieval based on matrix correlation

Abstract. Multiview learning is an important method and widely used for feature fusion in the fields of image process or big data analysis. Determining how to integrate compatible and complementary information from multiple views is a crucial and challenging task. We present a multiview feature fusion optimization method for image retrieval based on matrix correlation. This method first extracts four view features (Gist, histogram of color, pyramid histogram of oriented gradients, and multitrend structure descriptor) from the image. Then these features are, respectively, converted to different graph Laplacian matrices through local embedding. Third, a multiview feature alternating optimization process is constructed using matrix correlation statistics that adaptively combines the different view feature maps to a unified, low-dimensional embedding. Finally, the fusion feature is used for image retrieval experiments. Various experimental results show that the proposed algorithm is an effective method.
Decentralized Renewable Hybrid Mini-Grids for Rural Communities: Culmination of the IREP Framework and Scale up to Urban Communities

The Integrated Rural Energy Planning (IREP) framework offers a unified road map for locating, planning and operating decentralized renewable hybrid off-grid energy systems for localized (rural) applications in low-income countries. This paper presents the culmination of the IREP framework and aims to illustrate the final step of the IREP framework for two communities in Nigeria. It is focused on two aspects. Firstly, the techno-economic modeling (investment and operation optimization) of a hybrid mini-grid system using HOMER Pro, a techno-economic evaluation tool; and evaluating the benefits of demand side management (DSM) based on energy efficiency on the overall system economics using a scenario-based approach. Secondly, the conceptualization of a sustainable business model using the business model canvas scheme to deliver measurable socio-economic impacts in these communities. The results provide valuable insights into rural electrification via renewable hybrid mini-grids powered primarily with solar photovoltaic technology. Transcending mere electricity access, electricity is provided for productive uses (considering disaggregated end-uses) by harnessing other dispatchable renewable energy resources such as waste biomass. Given high share of rural population in developing countries, these insights are applicable in these regions and further the realization of the United Nations’ goal of sustainable energy (SDG7) and sustainable cities and communities (SDG11).
Implantatversorgung mit ZERAMEX XT bei Autoimmunerkrankung: ein Fallbericht

▶ Abb. 1 Röntgenaufnahme Implantatdarstellung vor Explantation. Quelle: Praxis Dr. C. Schulz Anamnestisch besteht seit etwas mehr als 20 Jahren eine Colitis ulcerosa (CU). Neben einer in diesem individuellen Fall erheblichen psychoemotionalen Belastung in der Kindheit und Jugend wird allgemein in der Literatur ein Zusammenwirken von mehreren fördernden Faktoren wie genetische Disposition und Umweltbelastung diskutiert, die zu einer Dysregulation des intestinalen Immunsystems führen [1].