Miracle-dz/UniFAR-FTUs huggingface dataset:
Carcass and Meat Quality of Male and Female Water Buffaloes Finished Under an Intensive Production System

Abstract Carcass and meat quality of male and female Anatolian water buffaloes were investigated using 10 carcasses from each gender. Gender had no influence on carcass characteristics, except warm carcass weight, which was 13% higher in males compared to females. Meat from male water buffaloes had higher ultimate pH and lightness (L*), but lower redness (a*) values than females. Meat samples aged for 21 days had lower values for expressed juice, cooking loss and Warner Bratzler shear force compared with those of 7-day aged ones. Meat samples aged for 21 days had higher L* value at 1 h and 24 h after cutting, a* value at 1 h after cutting compared with those of 7-day aged meat samples. Gender had no effect on meat sensory characteristics. Meat from male water buffaloes had higher proportions of C14:0, C18:3 n-3, C20:2 n-6, C20:3 n-3 and C20:4 n-6 and Σn-3 fatty acids and lower Σn-6/Σn-3 ratio compared with female water buffaloes.
A novel pooling layer based on gaussian function with wavelet transform

Convolution represent basic layer in the convolutional neural network, but it can result in big size of the data, which may increase the complexity of the network. Different pooling methods are used to perform down sample these data. In this paper, we have proposed a novel pooling method by using Gaussian function to determine the wavelet filter coefficients. At first, the basic statistics are determined for each pool size of the signal, then Gaussian probability distribution function is determined. According to the procedure of extracting the features, three methods are proposed, the first method is used the normalized values of basic statistics as wavelet filter to be multiplied by original signal, the second method used the determined statistics as features of the original signal, then multiplied it with constant wavelet filter based on Gaussian, while the third method is similar to first method, except it depend on entire signal instead of each pool size. The proposed methods are combined with other standard methods such as max and pooling. The experiments are performed on different datasets and the results show that the proposed methods perform or outperform other methods and can increase performance of the (CNN).
Multigene phylogeny and HPLC analysis reveal fake Ophiocordyceps sinensis in markets

Ophiocordyceps sinensis (Cordyceps sinensis) has long been a Chinese Traditional Medicine and functional food in China. Because of its valued medicinal effect and improvement in the Chinese economy, market demand for O. sinensis has significantly increased in recent years. Here, we use multigene and High Performance Liquid Chromatography (HPLC) analysis of specimens bought from markets to reveal the sale of fake O. sinensis in Traditional Chinese Medicine markets. The insect larvae (belonging to Lepidopteran) was a different species to that normally infected by O. sinensis. Combined sequence analysis of ITS, nrSSU, EF-1α and RPB1 gene markers also revealed the putative O. sinensis to be Metacordyceps taii. Producers had gone to great lengths to produce remarkably similar fake O. sinensis specimens. The insect body was infected with M. taii, but the fungus stromata were made from a Ligularia hodgsonii stem that had been molded into stromata and stuck into the insect body. We analyzed the nucleoside constitutes of the insect bodies and fake Cordyceps stromata which were very different to those of authentic wild O. sinensis samples from Tibet. It is not clear what the consumers of these products are actually ingesting and whether it may be harmful. In the future, sequence data should be used to test the authenticity of O. sinensis, and the development a real-time PCR assay for species-specific diagnosis is needed. The use of multi-gene phylogeny could have a wide application in verification of other Traditional Chinese Medicined and fungal biotechnology products.
Seasonal variation in diversity of marine benthic invertebrates leads to a positive species-genetic diversity correlation (SGDC)

We used the methods described by Thonig et al. (2017) to genotype Pygospio elegans at ten microsatellite loci. Since three of the loci showed Hardy-Weinberg deviations and null alleles (Thonig et al. 2017), they were excluded, and only details for the remaining seven loci are reported here. Briefly, genomic DNA was extracted from individual worms using the Qiagen DNeasy kit (Qiagen Nordic, Helsinki) following the manufacturer’s protocol. The microsatellite loci (Table 1) were amplified in two multiplex reactions using Qiagen’s Multiplex PCR kit (Qiagen Nordic, Helsinki). Multiplex reactions contained 1X Qiagen Multiplex Master mix and 0.2 μM of each primer. All amplification reactions were carried out in BioRad C1000 or S1000 thermocyclers (Bio-Rad Laboratories, Helsinki) with the following thermocycling program: 95 C for 15 min followed by 30 cycles of 94 C for 30 sec, 60 C for 90 sec and 72 C for 60 sec, terminating with a 30 min incubation at 60 C. One microliter of the amplification products were separated together with 0.09 μL GeneScan Liz500 size standard in Hi-Di formamide, using the ABI PRISM 3130xl machine (all Applied Biosystems; Thermo Scientific, Helsinki). Fragments were sized and genotypes assigned using GeneMapper v.3. 7. software (Applied Biosystems; Thermo Scientific, Helsinki) and manually checked for errors.
Mitochondrial DNA analysis of the domestic dogs in Turkey

Objective: This study aims to prove that analyzing the hypervariable I (HV-I) and HV-II regions of mitochondrial DNA using 150 blood samples from Canis lupus familiaris would be an important source of evidence in solving an incident. Materials and Methods: The target region was amplified in the first and second polymerase chain reaction step following DNA isolation and the purification process was performed. As for the sequence analysis, it was analyzed in the ABI3130 capillary electrophoresis device. The analysis of raw data was performed. The results obtained were compared with the reference sequence. Results: The results achieved are compatible with those of the previous studies and the polymorphisms in the positions 15,543 (4.03%), 15,640 (3.23%), 15,756 (6.45%), 15,945 (8.87%), 15,951 (%4.03), and 15,960 (3.23%) of the region HV-I and the positions 16,495 (16.94%), 16,585 (7.26%), 16,611 (15.32%), 16,619 (17.74%), 16,624 (12.90%), 16,628 (4.84%), 16,635 (8.06%), 16,637 (11.29%), 16,652 (4.84%), 16,654 (4.03%), 16,658 (13.71%), and 16,676 (4.03%) of the region HV-II were identified for the first time. Conclusions: This study is a first of its kind in the field of forensic science in Turkey; however, the run time and cost were reduced via optimization in a different way as compared to the methods used in international publications.
Land use planning in disputed mountain areas: conflicting interests and common arenas

Mountain areas are often subject to conflicts between different user interests and protection. The authors examine land use planning processes in Norway applied in accordance with the Planning and Building Act and the Nature Diversity Act and discuss how they might be improved. They find that although influenced by trends of decentralization, inclusion and integration, and principles for multilevel governance, the land use planning approaches for use and protection are still performed in the shadow of instrumentalism and hierarchy with little awareness of their limitations in practical use. The “communicative turn” has stimulated comprehensive participation processes, but these consensus-oriented processes have to some extent been able to handle conflicting interests. The authors conclude that in future planning it will be vital to establish common arenas as trading zones for coordinated municipal, regional and national planning, combining instrumental and communicative practices with agonistic approaches in a multilevel governance network.
The systemic activin response to pancreatic cancer: implications for effective cancer cachexia therapy

Pancreatic ductal adenocarcinoma (PDAC) is a particularly lethal malignancy with high rates of cachexia. Serum activin correlates with PDAC cachexia and mortality, while activin administration causes cachexia in mice. We studied activin in human tumors and in mice with orthotopic or genetic PDAC. Cachexia severity correlated with activin expression in tumor lines. Activins were expressed in both cancer and tumor stromal cells, but also in organs in murine PDAC cachexia. Tumor cells expressed activin-βA, or Inhba, while organs expressed both activin-βA and activin-βB, or Inhbb. PDAC elicits activin expression; PDAC conditioned medium induced activin and atrophy of myotubes. Treatment with the activin trap, ACVR2B/Fc, reduced cachexia and prolonged survival in mice with activin-low tumors, and reduced cachexia in activin-high tumors, without affecting activin expression in organs. Mice expressing dominant negative ACVR2B in muscle were protected for weight loss but not survival. Overall our results indicate that PDAC induces a systemic activin response, leading to cachexia, and that activin targets might include organs beyond muscle. Targeting of both tumor-derived and host-derived activins could improve cachexia therapy.
Synthesis and characterization of the novel 80S bioactive glass: bioactivity, ‎biocompatibility, cytotoxicity

In this research, the 80S bioactive glass with different Ca/P ratios was prepared by the sol-gel route. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transforms infrared spectroscopy (FTIR) were used to study the apatite structure and shape. According to the results, the 78SiO2–17P2O5–5CaO bioglass showed a higher rate of crystalline hydroxyapatite (HA) on its surface in comparison with the other bioglasses. After 3 days of immersion in the SBF solution, spherical apatite was formed on the 78SiO2–17P2O5–5CaO surface, which demonstrated high bioactivity. A statistically significant promotion in proliferation and differentiation of G292 osteoblastic cells was also observed. Regarding its optimal cell viability and bioactivity, the 78SiO2–17P2O5–5CaO bioactive glass could be offered as a promising candidate for bone tissue applications.
Extended-resolution acoustic imaging of low-frequency wave sources by acoustic analogy-based tomography

Abstract The weakest possible waves in nature are detectable by improving sensitive measurements, but the attainable imaging resolution of low-frequency waves is still challenging, especially in aeroacoustic experiments. In this work, we show how extended-resolution imaging of low-frequency wave sources can be achieved by incorporating acoustic analogy into tomography. First, an equivalent source of sound, which is dependent on the low-frequency target sound field, is produced due to the nonlinear coupling and interaction with an external high-frequency incident plane wave. Next, the low-frequency sources are reconstructed based on the induced sound waves recorded at the receivers. The induced sound waves are of high frequency to enable the extended-resolution imaging. The physical processes involved are theoretically explained based on the insightful acoustic analogy theory and the Born approximation. The numerical and experimental demonstration cases, with representative but straightforward configurations, show that the proposed method can identify the isolated target sources (at low frequencies) with a separation distance smaller than one-tenth to one-thirtieth of the wavelength, yielding much better resolution than the conventional acoustic imaging approaches. The results suggest that the proposed method will be a promising candidate to investigate the properties of an acoustic source within small regions, and, therefore, likely to be used in the study of the associated fluid physics.
Imaging object-scene integration in visible and invisible natural scenes

Integrating objects with their context is a key step in the interpretation of complex visual scenes. Humans can do this very quickly, yet the brain mechanisms that mediate this ability are not yet understood. Here, we used functional Magnetic Resonance Imaging (fMRI) to measure brain activity while participants viewed visual scenes depicting a person performing an action with an object that was either congruent or incongruent with the scene. Univariate and multivariate analyses revealed different activity for congruent compared to incongruent scenes in the lateral occipital complex, inferior temporal cortex, parahippocampal cortex, and prefrontal cortex, in line with existing models of scene processing. Importantly, and in contrast to previous studies, these activations could not be explained by task-induced conflicts. A secondary goal of this study was to examine whether object-context integration could occur in the absence of awareness, by comparing brain activity elicited by congruent vs. incongruent scenes that were suppressed from awareness using visual masking. We found no evidence for brain activity differentiating between congruent and incongruent invisible scenes. Overall, our results provide novel support for the roles of PHC and PFC in conscious object-context integration which cannot be explained by either low-level differences or task demands. Yet they further suggest that activity in these regions is decreased by visual masking to the point of becoming undetectable with our fMRI protocol.
Evaluating a neural network and a convolutional neural network for predicting soliton properties in a quantum noise environment

With its applications in science and engineering, supercontinuum (SC) generation is a phenomenon widely studied in nonlinear fiber optics. The SC spectral properties are not difficult to measure, except those related to time. Fortunately, machine learning can help predict the time behavior of various nonlinear optics phenomena using spectral characteristics. In this study, supervised machine learning tools are used to evaluate the prediction accuracy of the soliton properties in a noisy environment. A neural network (NN) and a convolutional neural network (CNN) are implemented to assess the performance of these techniques in relation to predicting soliton properties when noise is included in a laser that pumps a nonlinear fiber optics. We conclude that the CNN shows better performance compared with NN, as it involves more data with the same quantity of simulations conducted in both cases, whereas NN can better predict the target in the absence of noise.
Toroidal Metaphotonics and Metadevices

Toroidal moments in artificial media have received growing attention and considered as a promising framework for initiating novel approaches to manage intrinsic radiative losses in nanophotonic and plasmonic systems. In the past decade, there has been substantial attention on the characteristics and excitation methods of toroidal multipoles—in particular, toroidal dipole—in 3D bulk and planar metaplatforms. The remarkable advantages of toroidal resonances have thrust the toroidal metasurface technology from relative anonymity into the limelight, in which researchers have recently centered on developing applied optical and optoelectronic subwavelength devices based on toroidal metaphotonics and metaplasmonics. In this focused contribution, the key principles of 3D and flatland toroidal metastructures are described, and the revolutionary tools that have been implemented based on this topology are briefly highlighted. Infrared photodetectors, immunobiosensors, ultraviolet beam sources, waveguides, and functional modulators are some of the fundamental and latest examples of toroidal metadevices that have been introduced and studied experimentally so far. The possibility of the realization of strong plexciton dynamics and pronounced vacuum Rabi oscillations in toroidal plasmonic metasurfaces are also presented in this review. Ultimate efficient extreme‐subwavelength scale devices, such as low‐threshold lasers and ultrafast switches, are thus in prospect.
Towards effective monitoring of tropical phenology: maximizing returns and reducing uncertainty in long‐term studies

Phenology is a key component of ecosystem function and is increasingly included in assessments of ecological change. We consider how existing, and emerging, tropical phenology monitoring programs can be made most effective by investigating major sources of noise in data collection at a long‐term study site. Researchers at Lopé NP, Gabon, have recorded monthly crown observations of leaf, flower and fruit phenology for 88 plant species since 1984. For a subset of these data, we first identified dominant regular phenological cycles, using Fourier analysis, and then tested the impact of observation uncertainty on cycle detectability, using expert knowledge and generalized linear mixed modeling (827 individual plants of 61 species). We show that experienced field observers can provide important information on major sources of noise in data collection and that observation length, phenophase visibility and duration are all positive predictors of cycle detectability. We find that when a phenological event lasts >4 wk, an additional 10 yr of data increases cycle detectability by 114 percent and that cycle detectability is 92 percent higher for the most visible events compared to the least. We also find that cycle detectability is four times as high for flowers compared to ripe fruits after 10 yr. To maximize returns in the short‐term, resources for long‐term monitoring of phenology should be targeted toward highly visible phenophases and events that last longer than the observation interval. In addition, programs that monitor flowering phenology are likely to accurately detect regular cycles more quickly than those monitoring fruits, thus providing a baseline for future assessments of change.
Size‐Resolved Mixing States and Sources of Amine‐Containing Particles in the East China Sea

Single‐particle aerosol mass spectrometry was employed during a cruise campaign from 3 to 27 June 2017 to investigate the mixing states and sources of amine‐containing particles in the East China Sea. A total of 271,160 particles were successfully identified, and 19,861 of these particles contained amines. Monomethylamine (MMA), trimethylamine (TMA), and diethylamine (DEA) were the most abundant amines. They accounted for 50%, 16%, and 29%, respectively, of the amine‐containing particles. The size distributions (mean ± geometric standard deviation) of the MMA‐, TMA‐, and DEA‐containing particles peaked at 0.58 ± 0.12, 0.56 ± 0.10, and 0.40 ± 0.10 μm, respectively. Using an adaptive resonance theory neural network algorithm, four major clusters of amine‐containing particles were categorized: carbon‐rich particles, K‐rich particles, Na‐rich particles, and metal‐rich particles. The MMA‐containing particles contained abundant elemental carbon‐, K‐, Mn‐, and Fe‐rich particles, which exhibit higher concentrations in land air masses, indicating that the MMA mainly originated from terrestrial anthropogenic sources. The TMA‐containing particles contained abundant organic and elemental carbon‐, EC‐, K‐, and V‐rich particles. High concentrations of TMA‐containing particles were measured near ports, indicating the significant contribution of the ports. The DEA‐containing particles contained abundant organic and elemental carbon‐, K‐, Mn‐, Cu‐, and Na‐rich particles, and high concentrations of DEA‐containing particles were observed in remote marine areas, suggesting that both terrestrial anthropogenic and marine sources are important contributors to DEA‐containing particles.
Employee Reactions to Preservice Tips and Compliments

Preservice tips are becoming increasingly common in the marketplace (e.g., online food delivery, quick-service restaurants). While prior research has investigated how the practice of preservice tipping is perceived by customers, how preservice tipping impacts the perceptions and behaviors of employees remains unexplored. Does tipping early actually elicit better service? Through a series of four studies, our research compares the effectiveness of tips—a financial incentive, with compliments—a nonfinancial incentive. The results indicate that early tips and compliments are both effective in obtaining better service, but the relative effectiveness of a tip versus a compliment depends on the service context. In closed service contexts—which involve a continuous, relatively short interaction—tips are superior. For example, when getting a drink at a bar, buying a sandwich at a quick-service restaurant, or dropping off a car for valet parking, tipping early should lead to better customer service. In contrast, in open service contexts—which involve multiple interactions over a more extended period and provide an opportunity for a social connection—compliments become more effective. The results have practical implications for customers wishing to enhance their service experiences and for managers in motivating their employees.
Spatio-Temporal Changes of Housing Features in Response to Urban Renewal Initiatives: The Case of Seoul

Over the past two decades, Seoul has been in a transitional period in terms of urban renewal approaches. Housing is a fundamental element of citizens’ lives and the built landscape, thus, it deserves thoughtful scrutiny. As such, this study empirically investigates the dynamics of the spatial and temporal characteristics of housing stock within the context of new urban renewal policies in Seoul. A fine-grained and multifaceted analysis shows that the supply of new apartments has decreased over time, revealing that denser housing redevelopment in the inner city has become more difficult. In addition, an exploratory spatial data analysis indicates that although spatial clustering of old housing units has been reduced, new housing units have become more spatially distributed and outwardly dispersed over time. Since the physical and locational changes of housing stock are closely related to urban renewal initiatives, this study suggests that the city government needs to incorporate the concept of sustainable urban growth management into its housing supply and renewal policies.
Density-based Algorithms for Big Data Clustering Using MapReduce Framework

Clustering is used to extract hidden patterns and similar groups from data. Therefore, clustering as a method of unsupervised learning is a crucial technique for big data analysis owing to the massive number of unlabeled objects involved. Density-based algorithms have attracted research interest, because they help to better understand complex patterns in spatial datasets that contain information about data related to co-located objects. Big data clustering is a challenging task, because the volume of data increases exponentially. However, clustering using MapReduce can help answer this challenge. In this context, density-based algorithms in MapReduce have been largely investigated in the past decade to eliminate the problem of big data clustering. Despite the diversity of the algorithms proposed, the field lacks a structured review of the available algorithms and techniques for desirable partitioning, local clustering, and merging. This study formalizes the problem of density-based clustering using MapReduce, proposes a taxonomy to categorize the proposed algorithms, and provides a systematic and comprehensive comparison of these algorithms according to the partitioning technique, type of local clustering, merging technique, and exactness of their implementations. Finally, the study highlights outstanding challenges and opportunities to contribute to the field of density-based clustering using MapReduce.