Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerated Weathering Effects on Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and PHBV/TiO2 Nanocomposites

The effect of accelerated weathering on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and PHBV-based nanocomposites with rutile titanium (IV) dioxide (PHBV/TiO2) was investigated. The accelerated weathering test applied consecutive steps of UV irradiation (at 340 nm and 0.76 W m−2 irradiance) and moisture at 50 °C following the ASTM D4329 standard for up to 2000 h of exposure time. The morphology, chemical structure, crystallization, as well as the mechanical and thermal properties were studied. Samples were characterized after 500, 1000, and 2000 h of exposure time. Different degradation mechanisms were proposed to occur during the weathering exposure and were confirmed based on the experimental data. The PHBV surface revealed cracks and increasing roughness with the increasing exposure time, whereas the PHBV/TiO2 nanocomposites showed surface changes only after 2000 h of accelerated weathering. The degradation of neat PHBV under moisture and UV exposure occurred preferentially in the amorphous phase. In contrast, the presence of TiO2 in the nanocomposites retarded this process, but the degradation would occur simultaneously in both the amorphous and crystalline segments of the polymer after long exposure times. The thermal stability, as well as the temperature and rate of crystallization, decreased in the absence of TiO2. TiO2 not only provided UV protection, but also restricted the physical mobility of the polymer chains, acting as a nucleating agent during the crystallization process. It also slowed down the decrease in mechanical properties. The mechanical properties were shown to gradually decrease for the PHBV/TiO2 nanocomposites, whereas a sharp drop was observed for the neat PHBV after an accelerated weathering exposure. Atomic force microscopy (AFM), using the amplitude modulation–frequency modulation (AM–FM) tool, also confirmed the mechanical changes in the surface area of the PHBV and PHBV/TiO2 samples after accelerated weathering exposure. The changes in the physical and chemical properties of PHBV/TiO2 confirm the barrier activity of TiO2 for weathering attack and its retardation of the degradation process.
Bioefficacy of insecticides and biopesticides on banana leaf roller (Erionata torus Evans)

The recent havoc caused by the banana leaf roller, Erionata torus Evans in coastal parts of Karnataka on banana was leading to study the chemical management against this pest. A field experiment was conducted at Sirsi, Karnataka to study the efficacy of insecticides and biopesticides. Treatments like chlorpyriphos, profenophos, quinalphos and lambda cyhalothrin combined with dichlorvos, respectively and biopesticides like Nomuraea rileyi, Metarhizium anisopliae and Beauvaria bassiana mixed with neem oil 10,000 ppm @ 2ml/l were tested. Among the tested combinations lambda cyhalothrin + dichlorvos recorded least larval population of 5.48 larvae/plant (65.41% reduction) followed by chlorpyriphos + dichlorvos (60.80%) and profenophos + dichlorvos (57.22%). Among biopesticides N. rileyi (9.48 larvae/plant) and M. anisopliae (10.27 larvae/plant) recorded the least larval population. Among the management options, chemical management of the E. torus found promising. As an option lambda cyhalothrin, chlorpyriphos in combination with dichlorvos or biopesticides like N. rileyi and M. anisopliae in combination with neem oil may be recommended.
Q-LEARNING ALGORITHM PERFORMANCE FOR M-MACHINE , N-JOBS FLOW SHOP SCHEDULING PROBLEMS TO MINIMIZE MAKESPAN

Flow Shop Scheduling Problems circumscribes an important class of sequencing problems in the field of production planning. The problem considered here is to find a permutation of jobs to be sequentially processed on a number of machines under the restriction that the processing of each job has to be continuous with respect to the objective of minimizing the completion time of all jobs, known in literature as makespan or Cmax. This problem is as NP-hard, it is typical of combinatorial optimization and can be found in manufacturing environments, where there are conventional machines-tools and different types of pieces which share the same route. The following research presents a Reinforcement Learning algorithm known as Q-Learning to solve problems of the Flow Shop category. This algorithm is based on learning an action-value function that gives the expected utility of taking a given action in a given state where an agent is associated to each of the resources. To validate the quality of the solutions, test cases of the specialized literature are used and the results obtained are compared with the reported optimal results.
Measurement of Elastic Parameters of Lithium Hydroxylammonium Sulphate Single Crystal, by Ultrasonic Pulse Echo Overlap Technique

Ultrasonics is the most established and precise technique to determine the elastic parameters of materials. Elastic constants are important parameters of a crystal which provide valuable infor-mation about the bonding characteristic between adjacent atomic planes and the anisotropic cha-racter of the bonding and structural ability. Second order elastic constants can be measured by measuring the velocity of the ultrasonic pulses of different polarization along different symmetry directions. Elastic Constants of Lithium Hydroxylammonium Sulphate [LHAS] single crystal by ul-trasonic Pulse Echo Overlap [PEO] technique are reported for the first time. Large single crystals of LHAS of size [26×26×10] mm3 have been grown from supersaturated aqueous solution of the salt by slow evaporation technique over a period of 40 - 45 days at 305 K. Absolute velocities at room temperature (303 K) have been measured for the selected direction and modes with McSkimin criterion. The anisotropy in the elastic properties of LHAS is well studied by measuring ultrasonic velocity in the crystal in certain specified crystallographic directions. The elastic stiffness constants C11, C33, C44, C55, and C66, and Acoustic impedance constants and Rao’s constants in specified directions are evaluated.
Visual Simulation of Corrosion

This paper describes in one hand a computer graphics method for simulating corrosion imperfections on a single surface and in the other hand, presents briefly a more general 3D model. The method demonstrates the ability of the proposed 3D data structures for modeling realistic looking textures. We first propose a technique valid for generating the corrosion propagation on a single polygonal non-linear surface and the corrosion painting using a aqueous flow. The perspective of a more general model is then discussed. Finally, a series of examples illustrates the promising potential of this model.
Putative adult neurogenesis in palaeognathous birds: The common ostrich (Struthio camelus) and emu (Dromaius novaehollandiae)

In the current study, we examined adult neurogenesis throughout the brain of the common ostrich (Struthio camelus) and emu (Dromaius novaehollandiae) using immunohistochemistry for the endogenous markers PCNA which labels proliferating cells, and DCX, which stains immature and migrating neurons. The distribution of PCNA and DCX labelled cells was widespread throughout the brain of both species. The highest density of cells immunoreactive to both markers was observed in the olfactory bulbs and the telencephalon, especially the subventricular zone of the lateral ventricle. Proliferative hot spots, identified with strong PCNA and DCX immunolabelling, were identified in the dorsal and ventral poles of the rostral aspects of the lateral ventricles. The density of PCNA immunoreactive cells was less in the telencephalon of the emu compared to the common ostrich. Substantial numbers of PCNA immunoreactive cells were observed in the diencephalon and brainstem, but DCX immunoreactivity was weaker in these regions, preferentially staining axons and dendrites over cell bodies, except in the medial regions of the hypothalamus where distinct DCX immunoreactive cells and fibres were observed. PCNA and DCX immunoreactive cells were readily observed in moderate density in the cortical layers of the cerebellum of both species. The distribution of putative proliferating cells and immature neurons in the brain of the common ostrich and the emu is widespread, far more so than in mammals, and compares with the neognathous birds, and suggests that brain plasticity and neuronal turnover is an important aspect of cognitive brain functions in these birds.
The World Price of Credit Risk

Global asset pricing models have failed to capture the cross-section of country equity returns. Emerging markets display robust positive pricing errors, and country-level characteristics play a role in pricing international equities. This paper offers a risk-based explanation for such asset pricing deviations. A world credit risk factor is significantly priced in the cross-section of country equity returns. In its presence, the positive pricing errors in emerging markets disappear and country-level characteristics no longer play a role. The risk premium for exposure to the credit risk factor is 80 basis points per month and has increased in recent years.
Accelerating the Shuffle Phase to Speed up MapReduce Systems

The CPU-centric traditional network protocol processing limits the utilization of network bandwidth, even with the high speed network (100Gbps); and the situation is more obvious in big data systems. The high performance network technology-Remote Direct Memory Access(RDMA), has the benefit of directly accessing remote application’s memory without involving destination CPUs, broadening the performance boundary. In this paper, we build a pluggable shuffle module to boost the Map-Reduce system based on Unreliable Datagram transport of RDMA, including data fragmenting and a "Dynamic Controllably Apply and Allot" mechanism to ensure the reliability of data transmission. Experimental result shows that the performance of RDMA-based Spark is circa 16% better than that of IPoIB-based Spark.
Brain circuits signaling the absence of emotion in body language

Significance How do we infer absence of emotion? As opposed to the brain mechanisms for recognizing emotions, this issue has remained underinvestigated. Present findings bond communication between the amygdala and insula with the ability to infer the absence of emotion in body language. Previously, both the amygdala and insula have been associated with emotion perception. The outcome of this study extends the conceptualization of these brain regions and their interplay to the processing of social signals without emotional content. This may have wide-ranging implications for better understanding neuropsychiatric conditions characterized by misinterpretation of neutral for emotional signals, such as depression or schizophrenia. The findings call for interdisciplinary research on how the brain infers the lack of emotional valence in social signals. Adaptive social behavior and mental well-being depend on not only recognizing emotional expressions but also, inferring the absence of emotion. While the neurobiology underwriting the perception of emotions is well studied, the mechanisms for detecting a lack of emotional content in social signals remain largely unknown. Here, using cutting-edge analyses of effective brain connectivity, we uncover the brain networks differentiating neutral and emotional body language. The data indicate greater activation of the right amygdala and midline cerebellar vermis to nonemotional as opposed to emotional body language. Most important, the effective connectivity between the amygdala and insula predicts people’s ability to recognize the absence of emotion. These conclusions extend substantially current concepts of emotion perception by suggesting engagement of limbic effective connectivity in recognizing the lack of emotion in body language reading. Furthermore, the outcome may advance the understanding of overly emotional interpretation of social signals in depression or schizophrenia by providing the missing link between body language reading and limbic pathways. The study thus opens an avenue for multidisciplinary research on social cognition and the underlying cerebrocerebellar networks, ranging from animal models to patients with neuropsychiatric conditions.
Using Multi-System Monitoring Time Series to Predict Performance Events

The prediction of failures and other mission-critical events plays an important role in operating today’s software systems and has drawn the attention of many researchers. Event prediction is particularly challenging if multiple systems are involved. In this paper, we thus present an event prediction model which utilizes time series monitoring data from multiple software systems to predict performance events. Our approach incorporates a comprehensive, multi-system data preprocessing framework for creating various feature vector sets, which we then use to train a random forest classifier to evaluate our multi-system event prediction. Our preliminary evaluation based on data from monitoring 250 systems over a period of 20 days shows promising results.
High-strength Fe–20Mn–Al–C-based Alloys with Low Density

Mechanical properties of Fe-20Mn-(10-14)Al-(0-1.8)C (mass%) quaternary and Fe-20Mn-(10-14)Al-(0.75-1.8)C-5Cr (mass%) quinary alloys were investigated by hardness, cold-workability and tensile tests at room temperature. The γ(fcc) alloys in both quaternary and quinary systems with a low density of less than 7.0 g/cm 3 showed an excellent ductility and their hardness and tensile strength increased with increasing Al and C contents. The γ+α(bcc) duplex alloys also exhibited a high tensile strength by controlling the α volume fraction. TEM observation confirmed that high hardness and tensile strength of the alloys with high Al and C contents are caused by the precipitation of nano-size κ-carbide with perovskite structure during cooling from the annealing temperature. Fe-20Mn-11Al-1.8C-5Cr alloy with a density of 6.51 g/cm 3 showed a high specific strength of more than 180 MPa · cm 3 /g with a good tensile elongation of 40 %. The present Fe-20Mn-Al-C(-5Cr) alloys showed a higher specific strength than conventional steels.
Preliminary Assays towards Melanoma Cells Using Phototherapy with Gold-Based Nanomaterials

Cancer like melanoma is a complex disease, for which standard therapies have significant adverse side effects that in most cases are ineffective and highly unspecific. Thus, a new paradigm has come with the need of achieving alternative (less invasive) and effective therapies. In this work, biocompatible gold nanoparticles (GNPs) coated with hyaluronic acid and oleic acid were prepared and characterized in terms of size, morphology and cytotoxicity in the presence of Saccharomyces cerevisiae, and two cell lines, the keratinocytes (healthy skin cells, HaCat) and the melanoma cells (B16F10). Results showed that these GNPs absorb within the near-infrared region (750–1400 nm), in the optical therapeutic window (from 650 to 1300 nm), in contrast to other commercial gold nanoparticles, which enables light to penetrate into deep skin layers. A laser emitting in this region was applied and its effect also analyzed. The coated GNPs showed a spherical morphology with a mean size of 297 nm without cytotoxic effects towards yeast and tested cell lines. Nevertheless, after laser irradiation, a reduction of 20% in B16F10 cell line viability was observed. In summary, this work appears to be a promising strategy for the treatment of non-metastatic melanoma or other superficial tumors.
Eplet Mismatch Load and De Novo Occurrence of Donor-Specific Anti-HLA Antibodies, Rejection, and Graft Failure after Kidney Transplantation: An Observational Cohort Study.

BACKGROUND In kidney transplantation, evaluating mismatches of HLA eplets-small patches of surface-exposed amino acids of the HLA molecule-instead of antigen mismatches might offer a better approach to assessing donor-recipient HLA incompatibility and improve risk assessment and prediction of transplant outcomes. METHODS To evaluate the effect of number of eplet mismatches (mismatch load) on de novo formation of donor-specific HLA antibodies (DSAs) and transplant outcomes, we conducted a cohort study that included consecutive adult kidney recipients transplanted at a single center from March 2004 to February 2013. We performed retrospective high-resolution genotyping of HLA loci of 926 transplant pairs and used the HLAMatchmaker computer algorithm to count HLA eplet mismatches. RESULTS De novo DSAs occurred in 43 (4.6%) patients. Multivariable analysis showed a significant independent association between antibody-verified eplet mismatch load and de novo DSA occurrence and graft failure, mainly explained by DQ antibody-verified eplet effects. The association with DQ antibody-verified eplet mismatches was linear, without a safe threshold at which de novo DSA did not occur. Odds for T cell- or antibody-mediated rejection increased by 5% and 12%, respectively, per antibody-verified DQ eplet mismatch. CONCLUSIONS Eplet mismatches in HLA-DQ confer substantial risk for de novo DSA formation, graft rejection, and graft failure after kidney transplantation. Mismatches in other loci seem to have less effect. The results suggest that antibody-verified HLA-DQ eplet mismatch load could be used to guide personalized post-transplant immunosuppression. Adoption of molecular matching for DQA1 and DQB1 alleles could also help to minimize de novo DSA formation and potentially improve transplant outcomes.
Effects of methylparaben on in vitro maturation of porcine oocytes

Parabens (PBs) are compounds widely used in industry for food and personal care products as antimicrobials and preservatives. Their indiscriminate use has resulted in their detection in different ecosystems so that humans and other organisms are highly exposed. Methylparaben (MePB), compared with other PBs, is mostly detected in food, personal care and baby care products. PBs could be linked to the generation of hormonal disorders and fertility impairment since their recent classification as endocrine disruptors. The knowledge of the effects that MePB can exert is of great importance as, in terms of reproduction, information is limited. Therefore, the objective of the present study was to evaluate the effect of MePB on porcine oocyte viability and in vitro maturation (IVM), as well as to determine the lethal concentration at 50% (LC50) and the maturation inhibition concentration at 50% (MIC50). Oocytes were exposed to different MePB concentrations 0 (control), 50, 100, 500, 750 and 1000 μm during 44 h of IVM. Cytoplasmic alterations and reduced cumulus cell expansion were observed in oocytes exposed to MePB; however, viability was not affected. In addition, oocyte maturation decreased in a concentration‐dependent manner after exposure to MePB. The estimated LC50 was 2028.38 μm, whereas MIC50 was 780.31 μm. To our knowledge, this is the first study that demonstrates that MePB altered porcine oocyte morphology, and caused a reduction in cumulus cell expansion, both of which resulted in decreased oocyte maturation. Therefore, MePB exposure may be one of the factors involved in fertility impairment in mammals, including that of humans.
A Generalized Simulation Framework for Tethered Remotely Operated Vehicles in Realistic Underwater Environments

This paper presents a framework for simulating visually realistic motion of underwater Remotely Operated Vehicles (ROVs) in highly complex models of aquatic environments. The models include a wide range of objects such as rocks, fish and marine plankton in addition to an ROV tether. A modified cable simulation for the underwater physical conditions has been developed for a tethered ROV. The simulation framework also incorporates models for low visibility conditions and intrinsic camera effects unique to the underwater environment. The visual models were implemented using the Unreal Engine 4 realistic game engine to be part of the presented framework. We developed a generalized method for implementing an ROV dynamics model and this method serves as a highly configurable component inside our framework. In this paper, we explore the unique characteristics of underwater simulation and the specialized models we developed for that environment. We use computer vision algorithms for feature extraction and feature tracking as a probe for comparing experiments done in our simulated environment against real underwater experiments. The experimental results presented in this paper successfully demonstrate the contribution of this realistic simulation framework to the understanding, analysis and development of computer vision and control algorithms to be used in today’s ROVs.
Drivers of Sustainable Supply Chain Management: Identification and Classification

With the increase in awareness of environmental and social issues associated with the development and the use of products, stakeholders—especially consumers—are showing more concern regarding these issues. To address new developments and changing trends, organizations are now compelled to identify and implement innovative and sustainable solutions, not only within their organizations’ boundaries, but also across the whole supply chain network. The primary goal of this paper was to identify and analyze drivers of sustainable supply chain management (SSCM) that influence or encourage organizations to undertake sustainability initiatives and implement sustainable solutions throughout their supply chains. For this purpose, a systematic literature review was conducted and 1559 drivers of SSCM were identified from 217 journal articles. Precise interpretation, clear definitions, restructuring, and classification into external and internal driver categories produced a list of 40 unique drivers of SSCM. The results revealed that regulatory and market pressures, with reference to the number of citations, are the most prevailing drivers of SSCM for the implementation of sustainability practices. Classification of the drivers of SSCM into primary and secondary driver categories may assist practitioners and decision makers in prioritizing sustainability-related initiatives and adopting sustainability practices across the whole supply chain network.
Università degli Studi di Padova Dipartimento di Ingegneria dell ’ Informazione Corso di Laurea Magistrale in Ingegneria Informatica Tesi di Laurea Parallel Stack Distance Computation for the Least Recently Used Replacement Policy

Storage hierarchies have been a staple in the organization of the memory in a computer system. Faster levels of memory are placed closer to the CPU, while further devices have higher storage capacity, but take considerably more time to access. In this work we focus on caches, and specifically on the stack distance computation problem. This problem involves the calculation of the minimum cache capacity containing a given page reference encountered while processing the address trace of a computer program. Stack distance computation has been widely investigated for a single processor; our objective is to design a parallel algorithm in order to speedup this operation. To this end, we present a theoretical framework which involves Finite State Machines and prefix computation on semigroups. With this framework, we have focused on the LRU policy and developed a parallel algorithm capable of analyzing a trace of L references to V distinct addresses in time O((L log V )/P ), when executed by P ≤ L/V processors. This represents a linear speedup with respect to the best known sequential algorithm. We have implemented our algorithm in C++ and evaluated its performances on an IBM Power 770 machine.