Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of intramammary infections and relationship with somatic cell counts in Italian buffaloes

INTRODUCTION World milk production has doubled in the last decades and it is noteworthy that in the last years, buffaloes have been supplying about 12% of the world milk production. India and Pakistan have been producing 60 and 30%, respectively, of the world’s buffalo milk. In both these countries buffalo milk contributes to 55 and 75% of the total milk produced (FAO, 2004). Dairy buffalo production has been a tradition in many parts of the world like the Caucasian countries, Asia, and Egypt where fresh buffalo milk, dahi (cultured sour milk), ghee (butter oil), and yoghurt are popular. In Italy the dairy buffalo industry is flourishing on account of the popularity of buffalo mozzarella cheese. that is the first buffalo milk producer in Europe. Italian River Buffalo (Bubalus bubalis) rearing is historically proper of middle and southern regions. In recent years there has been a trend to install this kind of rearing in the north of Italy, trying to encounter consumers interest and, above all, avoiding restriction imposed by the European Community quotas policy to bovine farmers. As well as cows also for dairy buffaloes the most frequent disease and the main cause of loss is mastitis, although their apparent rusticity. The loss in milk production is even more evident and remarkable as buffaloes yield every day only about 8 litres. Elevate somatic cell count (SCC) is associated with a reduced milk yield and a clear alteration in milk components concentration (Harmon, 1994; Piccinini et al., 2006). Until now few studies have dealt Como citar este capitulo: CLARA, M.P.L. Prevalence of intramamary infections and relationship with somatic cell counts in Italian buffaloes. In: BARBOSA, S.B. P., BATISTA, A.M.V. , MONARDES, H. III Congresso Brasileiro de Qualidade do Leite. Recife: CCS Grafica e Editora, 2008, v.1, p. 343-349.
ANALYSIS OF APS READOUT CIRCUIT DELAY

The paper provides a complete analysis of the APS pixel and column circuit delay. Contrary to common belief, we show that shorter settling times can be achieved by reducing the bias current and hence reducing energy consumption. We then investigate the effect of non-idealities on the readout operation. We find that when the follower transistor channel length modulation is taken into consideration, delay is reduced, which implies that shorter length transistors can be used in the pixel. As expected, we find that delay decreases linearly with technology scaling.
Clinical and pathological perspectives on elbow arthritis and arthroplasty

The basic design of replacement arthroplasty components for treating arthritis in the hip, knee and shoulder had been established by the end of the 1970s/early 1980s. Replacement arthroplasty components for elbow arthritis were being developed at the same time, but a wide variety of designs were manufactured, and the basic design characteristics required for a successful elbow joint arthroplasty remain a matter of debate today. Whereas the number of total elbow joint replacements (TERs) performed for elbow fractures has increased steadily over recent years, the reverse is true in arthritis surgery where there has been a steady decline. We explain this in terms of how our understanding of the pathology and evolution of degenerative changes in the elbow over the past 40 years have influenced our perspectives on the design of elbow arthroplasty components for arthritis and the predilection of the degenerative changes for the lateral (radiocapitellar) compartment of the elbow joint. This has led to the concept of unicompartmental elbow replacement and development of components to resurface the lateral compartment of the elbow [lateral resurfacing elbow (LRE) arthroplasty]. We now believe that the future direction of elbow arthroplasty lies in the further development of components to resurface specifically only those areas of articular cartilage destroyed by the disease process in an individual elbow joint and the development of ‘anatomical designs’ of TER with replaceable bearing surfaces for those joints in which the areas of cartilage destruction are more
Increasing the Accuracy of NEWFM using a Geometric Graph-Based Gene Selection Algorithm

In a microarray dataset with thousands of genes, the majority of the genes are irrelevant to the occurrence of disease. One of the challenges in analyzing microarray datasets is selecting a suitable number of the most relevant genes with maximum classification accuracy. A neural network with weighted fuzzy membership functions (NEWFM) is a supervised neuro-fuzzy system that reduces the size of available data to improve classification accuracy and computational efficiency. This paper proposes a new gene selection algorithm based on a geometric graph using the bounded sum of weighted fuzzy membership functions (BSWFM) that improves the accuracy of NEWFM. The proposed gene selection algorithm reduces computational load and improves accuracy by removing irrelevant genes using the Euclidean distances of the centers of gravity multiplied by the non-overlap area between two BSWFMs. Further, the results of comparative experiments conducted using the colon cancer and the leukemia microarray problem datasets indicate that NEWFM with the proposed gene selection algorithm is more accurate than NEWFM without the proposed algorithm. More specifically, 2000 genes from the colon cancer dataset and 7129 genes from the leukemia dataset used as inputs to NEWFM without the proposed algorithm resulted in accuracies of 90.3% and 58.8%, respectively. In contrast, inputs of seven minimum genes from the colon cancer dataset and nine minimum genes from the leukemia dataset to NEWFM with the proposed algorithm resulted in accuracies of 96.8% and 100%, respectively.
The Trade-Offs of Private Prediction

Machine learning models leak information about their training data every time they reveal a prediction. This is problematic when the training data needs to remain private. Private prediction methods limit how much information about the training data is leaked by each prediction. Private prediction can also be achieved using models that are trained by private training methods. In private prediction, both private training and private prediction methods exhibit trade-offs between privacy, privacy failure probability, amount of training data, and inference budget. Although these trade-offs are theoretically well-understood, they have hardly been studied empirically. This paper presents the first empirical study into the trade-offs of private prediction. Our study sheds light on which methods are best suited for which learning setting. Perhaps surprisingly, we find private training methods outperform private prediction methods in a wide range of private prediction settings.
Effect of dietary flavonoids on pathways involved in drug metabolism

Flavonoids are a large group of plant polyphenols with presumed beneficial effects on several common diseases. The use of dietary supplements enriched with flavonoids is becoming increasingly popular. These polyphenols are substrates of enzymes like cytochrome P450 monooxygenases and phase II conjugation enzymes, as well as of drug transporters involved in drug excretion. Thus, they share the same metabolic pathways with many therapeutic drugs. A number of studies have demonstrated inhibition of various cytochrome P450 monooxygenases and drug transporters by flavonoids. Flavonoid-induced effects on drug bioavailability were also shown. This raises concerns about the safe use of flavonoid supplements and flavonoid-containing remedies which are not subject to legal regulations. The challenge is to find a suitable way to predict harmful drug-flavonoid interactions.
THE EXISTENCE AND UNIQUENESS OF THE SOLUTION FOR NONLINEAR FREDHOLM AND VOLTERRA INTEGRAL EQUATIONS VIA ADAPTING-CEILING DISTANCES

The purpose of this work is to introduce the new contractive condition which involves mw-distances in metric spaces. The fixed point theorems for mappings satisfying such contractive condition are established via the idea of an adapting-ceiling distance. Two illustrative examples are also given to confirm that our results rightly generalize many results in the literatures. As an application, the existence and uniqueness of the solution for nonlinear Fredholm integral equations and nonlinear Volterra integral equations are investigated via our main result.
Behavioral analysis of support vector machine classifier with Gaussian kernel and imbalanced data

The parameters of support vector machines (SVMs) such as the penalty parameter and the kernel parameters have a great impact on the classification accuracy and the complexity of the SVM model. Therefore, the model selection in SVM involves the tuning of these parameters. However, these parameters are usually tuned and used as a black box, without understanding the mathematical background or internal details. In this paper, the behavior of the SVM classification model is analyzed when these parameters take different values with balanced and imbalanced data. This analysis including visualization, mathematical and geometrical interpretations and illustrative numerical examples with the aim of providing the basics of the Gaussian and linear kernel functions with SVM. From this analysis, we proposed a novel search algorithm. In this algorithm, we search for the optimal SVM parameters into two one-dimensional spaces instead of searching into one two-dimensional space. This reduces the computational time significantly. Moreover, in our algorithm, from the analysis of the data, the range of kernel function can be expected. This also reduces the search space and hence reduces the required computational time. Different experiments were conducted to evaluate our search algorithm using different balanced and imbalanced datasets. The results demonstrated how the proposed strategy is fast and effective than other searching strategies.
Monaural Singing Voice and Accompaniment Separation Based on Gated Nested U-Net Architecture

This paper proposes a separation model adopting gated nested U-Net (GNU-Net) architecture, which is essentially a deeply supervised symmetric encoder–decoder network that can generate full-resolution feature maps. Through a series of nested skip pathways, it can reduce the semantic gap between the feature maps of encoder and decoder subnetworks. In the GNU-Net architecture, only the backbone not including nested part is applied with gated linear units (GLUs) instead of conventional convolutional networks. The outputs of GNU-Net are further fed into a time-frequency (T-F) mask layer to generate two masks of singing voice and accompaniment. Then, those two estimated masks along with the magnitude and phase spectra of mixture can be transformed into time-domain signals. We explored two types of T-F mask layer, discriminative training network and difference mask layer. The experiment results show the latter to be better. We evaluated our proposed model by comparing with three models, and also with ideal T-F masks. The results demonstrate that our proposed model outperforms compared models, and it’s performance comes near to ideal ratio mask (IRM). More importantly, our proposed model can output separated singing voice and accompaniment simultaneously, while the three compared models can only separate one source with trained model.
Alpine Scenedesmaceae from New Zealand: new taxonomy

Cultures from samples collected from the alpine zone in Canyon Creek, Canterbury, New Zealand, revealed three taxa belonging to Scenedesmaceae. Identifications were made based on morphological data (light microscopy and transmission and scanning electron microscopy) and sequences of 18S ribosomal DNA. Desmodesmus abundans is a commonly recorded species worldwide and in New Zealand, but Desmodesmus granulatus is a new record for this country. Coelastrella multistriata var. grandicosta is described as new to science. Cryptodesmus ellipsoideus, previously isolated from the alpine zone at Arthur's Pass, is transferred to Coelastrella ellipsoidea on the basis of new ultrastructural and molecular information. Analysis of 18S ribosomal DNA in Coelastrella indicates likely intragenomic recombination and possible horizontal transfer of introns between taxa in this genus. http://zoobank.org/urn:lsid:zoobank.org:pub:2D9CA9F7-72DE-462B-8201-2725F4F9C91F
Disturbance Rejection with Highly Oscillating Second-order-like Process, Part IV: I-PD Controller

This paper investigates the possibility of using an I-PD controller for the purpose of disturbance rejection associated with a highly oscillating second-order-like process. The MATLAB control and optimization toolboxes are used to tune the I-PD controller parameters to achieve optimal performance of the linear control system excited by process unit step disturbance. Three objective functions based on the time response error of the control system are used, and the best function is assigned. The simulation results show the effectiveness of the I-PD controller and its tuning approach in rejecting the disturbance associated with such high oscillating processes. The ITAE objective function is appropriate for use with the I-PD controller and the highly oscillating process. It is possible to go with the maximum time response to as low level as 1.5 x 10 at a time of only 3.4 ms. The studied controller is capable of competing with other types used in this series of papers such as PD-PI and PI-PD controllers.
Ca2+ Signaling in Cardiac Myocytes Overexpressing the &agr;1 Subunit of L-Type Ca2+ Channel

Voltage-gated L-type Ca2+ channels (LCCs) provide Ca2+ ingress into cardiac myocytes and play a key role in intracellular Ca2+ homeostasis and excitation-contraction coupling. We investigated the effects of a constitutive increase of LCC density on Ca2+ signaling in ventricular myocytes from 4-month-old transgenic (Tg) mice overexpressing the &agr;1 subunit of LCC in the heart. At this age, cells were somewhat hypertrophic as reflected by a 20% increase in cell capacitance relative to those from nontransgenic (Ntg) littermates. Whole cell ICa density in Tg myocytes was elevated by 48% at 0 mV compared with the Ntg group. Single-channel analysis detected an increase in LCC density with similar conductance and gating properties. Although the overexpressed LCCs triggered an augmented SR Ca2+ release, the “gain” function of EC coupling was uncompromised, and SR Ca2+ content, diastolic cytosolic Ca2+, and unitary properties of Ca2+ sparks were unchanged. Importantly, the enhanced ICa entry and SR Ca2+ release were associated with an upregulation of the Na+-Ca2+ exchange activity (indexed by the half decay time of caffeine-elicited Ca2+ transient) by 27% and SR Ca2+ recycling by ≈35%. Western analysis detected a 53% increase in the Na+-Ca2+ exchanger expression but no change in the abundance of ryanodine receptor (RyR), SERCA2, and phospholamban. Analysis of ICa kinetics suggested that SR Ca2+ release-dependent inactivation of LCCs remains intact in Tg cells. Thus, in spite of the modest cardiac hypertrophy, the overexpressed LCCs form functional coupling with RyRs, preserving both orthograde and retrograde Ca2+ signaling between LCCs and RyRs. These results also suggest that a modest but sustained increase in Ca2+ influx triggers a coordinated remodeling of Ca2+ handling to maintain Ca2+ homeostasis.
Learn to Use Future Information in Simultaneous Translation

Simultaneous neural machine translation (briefly, NMT) has attracted much attention recently. In contrast to standard NMT, where the NMT system can utilize the full input sentence, simultaneous NMT is formulated as a prefix-to-prefix problem, where the system can only utilize the prefix of the input sentence and more uncertainty is introduced to decoding. Wait-$k$ is a simple yet effective strategy for simultaneous NMT, where the decoder generates the output sequence $k$ words behind the input words. We observed that training simultaneous NMT systems with future information (i.e., trained with a larger $k$) generally outperforms the standard ones (i.e., trained with the given $k$). Based on this observation, we propose a framework that automatically learns how much future information to use in training for simultaneous NMT. We first build a series of tasks where each one is associated with a different $k$, and then learn a model on these tasks guided by a controller. The controller is jointly trained with the translation model through bi-level optimization. We conduct experiments on four datasets to demonstrate the effectiveness of our method.
Microarchitecture Online Template Attacks.

Online template attack (OTA) is a powerful technique previously used to attack elliptic curve scalar multiplication algorithms. This attack has been only analyzed in the realm of power-consumption and EM side-channels, where the signals leak about the value to be processed. However, no microarchitecture analysis variant has been proposed, especially considering the different nature between power-consumption signals and microarchitecture-based ones. In this paper we start filling this gap by revisiting the original OTA description, proposing a generic framework and evaluation metrics for any side-channel signal. Our analysis reveals OTA features not covered before, increasing its application scenarios that requires revisiting original countermeasures to prevent it. In this regard we demonstrate that OTA can work in the backward direction allowing to mount an augmented projective coordinates attack wrt the proposed by Naccache et al. (Eurocrypt 2004). We analyze three libraries libgcrypt, mbedTLS, and wolfSSL using two microarchitecture side-channels. For the libgcrypt case we target its EdDSA implementation using Curve25519 twist curve. We obtain similar results for mbedTLS and wolfSSL with curve secp256r1. For each library we execute extensive attack instances being able to recover the complete scalar in all cases using a single trace. In this work demonstrate that microarchitecture online template attacks are also very powerful in this scenario, recovering secret information without knowing a leakage model. This highlights the importance of developing secure-by-default implementations, instead of fix-on-demand ones.
In vitro Regeneration of the Medicinal Plant, Plumbago zeylanica L. with Reference to a Unique Population in Maruthamalai, the Western Ghats, India

The in vitro regeneration of Plubago zeylanica exhibited that the callus was initiated in the basal medium containing BAP, NAA, 2, 4-D, and IBA. The high amount (90%) of organic calli was induced in the basal medium supplemented with 2, 4-D, alone at 2.0 mg/l. In the subculture the adventitious shoot formation was prominently higher (83%) in the basal medium containing BAP, and NAA at 3.5 and 0.3 mg/l, respectively. IAA (1.0 mg/l)effectively produced higher percen-tage (90) of roots and root growth. After sequential hardening, survivability rate was observed to be significantly higher (80%) in the hardening medium containing garden soil, sand and vermicompost in the ratio of 1 : 1 : 1 by volume under greenhouse condition. Key words: Plumbago zeylanica , In vitro regeneration, Medicinal plant D.O. I. 10.3329/ptcb.v18i2. 3648 Plant Tissue Cult. & Biotech. 18 (2): 173-179, 2008 (December)
On the identity of the freshwater dinoflagellate Glenodinium edax, with a discussion on the genera Tyrannodinium and Katodinium, and the description of Opisthoaulax gen. nov.

Calado A.J. 2011. On the identity of the freshwater dinoflagellate Glenodinium edax, with a discussion on the genera Tyrannodinium and Katodinium, and the description of Opisthoaulax gen. nov. Phycologia 50: 641–649. DOI: 10.2216/11-21.1 Within the context of the preparation of a flora for the identification of freshwater dinoflagellates, the identity of Glenodinium edax and the affinities of a group of phagotrophic species with a conspicuous eyespot not associated with plastids (eyespot type C) currently classified in Katodinium were re-evaluated. The original description and illustrations of the phagotrophic G. edax suggest affinity with the Pfiesteriaceae. Whereas the tabulation currently associated with G. edax is based on a probable misidentification, the similarity to Tyrannodinium berolinense suggests that the two names can be regarded as synonyms and T. edax comb. nov. is proposed. As presented in modern floras, Katodinium is artificially defined on the basis of the position of the cingulum at or below the posterior third of the cell, and includes widely different forms. The presence of an eyespot of type C in the phagotrophic Katodinium vorticella and related species combines with a general cell morphology reminiscent of Esoptrodinium gemma and the formation of Tovellia-like cysts to mark this group of species as belonging to the Tovelliaceae. The type species of Katodinium, K. nieuportense, is morphologically quite different from these species and does not display tovelliacean characters. None of the known genera of Tovelliaceae matches the characters of K. vorticella and its close relatives. Opisthoaulax gen. nov. is described and new combinations are proposed for K. vorticella and six other species.
Radiation spectra and effective temperatures in higher-dimensional charged de Sitter black holes

In this study, a scalar field propagating in a higher-dimensional Reissner-Nordstrom-de Sitter black hole is investigated. The scalar fields are assumed to have non-minimal coupling to the brane or bulk scalar curvature. Five different notations of black hole temperatures are discussed: temperature based on surface gravity, Bousso-Hawking temperature, and three effective temperatures. The greybody factors of minimally and non-minimally coupled scalar fields on the brane and in the bulk are examined under the effect of particle and spacetime properties. The energy emission spectra of the black holes are determined at various temperatures for both the brane and bulk channels. It was observed that the energy emission rates at the Bousso-Hawking temperature dominate over those at other temperatures. The energy emission curves are suppressed by the presence of the coupling parameters. Finally, the bulk-over-brane emission ratios are computed. It was noted that for a certain definition of the temperatures and regime of the cosmological constant, bulk dominance becomes possible.
VRUNet: Multi-Task Learning Model for Intent Prediction of Vulnerable Road Users

Advanced perception and path planning are at the core for any self-driving vehicle. Autonomous vehicles need to understand the scene and intentions of other road users for safe motion planning. For urban use cases it is very important to perceive and predict the intentions of pedestrians, cyclists, scooters, etc., classified as vulnerable road users (VRU). Intent is a combination of pedestrian activities and long term trajectories defining their future motion. In this paper we propose a multi-task learning model to predict pedestrian actions, crossing intent and forecast their future path from video sequences. We have trained the model on naturalistic driving open-source JAAD [1] dataset, which is rich in behavioral annotations and real world scenarios. Experimental results show state-of-the-art performance on JAAD dataset and how we can benefit from jointly learning and predicting actions and trajectories using 2D human pose features and scene context.