Miracle-dz/UniFAR-FTUs huggingface dataset:
One-year experiment on the physiological response of the Mediterranean crustose coralline alga, Lithophyllum cabiochae, to elevated pCO2 and temperature

The response of respiration, photosynthesis, and calcification to elevated pCO2 and temperature was investigated in isolation and in combination in the Mediterranean crustose coralline alga Lithophyllum cabiochae. Algae were maintained in aquaria during 1 year at near-ambient conditions of irradiance, at ambient or elevated temperature (+3°C), and at ambient (ca. 400 μatm) or elevated pCO2 (ca. 700 μatm). Respiration, photosynthesis, and net calcification showed a strong seasonal pattern following the seasonal variations of temperature and irradiance, with higher rates in summer than in winter. Respiration was unaffected by pCO2 but showed a general trend of increase at elevated temperature at all seasons, except in summer under elevated pCO2. Conversely, photosynthesis was strongly affected by pCO2 with a decline under elevated pCO2 in summer, autumn, and winter. In particular, photosynthetic efficiency was reduced under elevated pCO2. Net calcification showed different responses depending on the season. In summer, net calcification increased with rising temperature under ambient pCO2 but decreased with rising temperature under elevated pCO2. Surprisingly, the highest rates in summer were found under elevated pCO2 and ambient temperature. In autumn, winter, and spring, net calcification exhibited a positive or no response at elevated temperature but was unaffected by pCO2. The rate of calcification of L. cabiochae was thus maintained or even enhanced under increased pCO2. However, there is likely a trade-off with other physiological processes. For example, photosynthesis declines in response to increased pCO2 under ambient irradiance. The present study reports only on the physiological response of healthy specimens to ocean warming and acidification, however, these environmental changes may affect the vulnerability of coralline algae to other stresses such as pathogens and necroses that can cause major dissolution, which would have critical consequence for the sustainability of coralligenous habitats and the budgets of carbon and calcium carbonate in coastal Mediterranean ecosystems.
RNA-Seq Analysis Reveals MAPKKK Family Members Related to Drought Tolerance in Maize

The mitogen-activated protein kinase (MAPK) cascade is an evolutionarily conserved signal transduction pathway that is involved in plant development and stress responses. As the first component of this phosphorelay cascade, mitogen-activated protein kinase kinase kinases (MAPKKKs) act as adaptors linking upstream signaling steps to the core MAPK cascade to promote the appropriate cellular responses; however, the functions of MAPKKKs in maize are unclear. Here, we identified 71 MAPKKK genes, of which 14 were novel, based on a computational analysis of the maize (Zea mays L.) genome. Using an RNA-seq analysis in the leaf, stem and root of maize under well-watered and drought-stress conditions, we identified 5,866 differentially expressed genes (DEGs), including 8 MAPKKK genes responsive to drought stress. Many of the DEGs were enriched in processes such as drought stress, abiotic stimulus, oxidation-reduction, and metabolic processes. The other way round, DEGs involved in processes such as oxidation, photosynthesis, and starch, proline, ethylene, and salicylic acid metabolism were clearly co-expressed with the MAPKKK genes. Furthermore, a quantitative real-time PCR (qRT-PCR) analysis was performed to assess the relative expression levels of MAPKKKs. Correlation analysis revealed that there was a significant correlation between expression levels of two MAPKKKs and relative biomass responsive to drought in 8 inbred lines. Our results indicate that MAPKKKs may have important regulatory functions in drought tolerance in maize.
Double Chins and Double Standards: A Meta-Analysis of Weight-Based Bullying Amongst Female Adolescents

Scholars are beginning to explore and understand the experiences of adolescent females in regards to weight-based bullying in their elementary school setting (Puhl, R. M., Luedicke, J., & Heuer, C. (2011). Weight-based victimization toward overweight adolescents: observations and reactions of peers. Journal of School Health, 81(11), 696703). The educational and social implications that weight-based bullying has amongst female adolescents can include: poor academic achievement coupled with a low degree of comfort when participating vocally in the classroom, the inability to initiate and maintain friendships, and an unwillingness to participate in extracurricular sports and activities. This should be cause for concern among the enthusiastic and focused teachers who are committed to giving young students, particularly females, the best possible education in life. A meta-analysis was used to guide the following three questions: (1) What are the different implications, both educational and social, that weight-based bullying has on male and female students, respectively? (2) What types of support do the participants seek from their teachers, administrators, and parents, to address this phenomenon? (3) How effective are school initiatives, such as bystander initiatives, in bettering the experiences of adolescent females who are experiencing weight-based bullying in an educational setting? Useful recommendations found throughout this Major Research Paper aim to provide support through in-school programming to students that are experiencing weight-based bullying.
Neural substrates of verbal memory impairments in adults with type 2 diabetes mellitus

Background: Verbal memory impairment is well documented in type 2 diabetes mellitus (T2DM) but, to date, the neural substrates remain unclear. The present study evaluated verbal memory and ascertained the degree of frontal and temporal lobe involvement in the anticipated verbal memory impairment among adults with T2DM. Method: Forty-six late-middle-aged and elderly adults with T2DM and 50 age-, sex-, and education-matched adults without T2DM underwent medical evaluation, verbal memory assessment, and brain magnetic resonance imaging (MRI) evaluations. Results: As anticipated, participants with T2DM had clear verbal memory impairments. Consistent with prior reports, we found volume reductions restricted to the hippocampus. Our diffusion tensor imaging analysis revealed that participants with T2DM had extensive cerebral gray and white matter microstructural abnormalities predominantly in the left hemisphere, with a larger concentration present in the temporal lobe. In contrast, we uncovered mostly nonspecific microstructural abnormalities in the absence of tissue loss in the frontal lobe. Of great importance, we present the first evidence among participants with T2DM linking verbal memory impairment and compromised microstructural integrity of the left parahippocampal gyrus, a key memory-relevant structure. Conclusions: Our results suggest that the hippocampus and parahippocampal gyrus may be particularly vulnerable to the deleterious effects of T2DM. The parahippocampal gyrus in particular may play a crucial role in the verbal memory impairments frequently reported in T2DM. Future studies should employ methods such as resting state functional magnetic resonance imaging and diffusion tensor imaging tractography to better characterize network connectivity, which may help further characterize the verbal memory impairment frequently reported in T2DM.
Cross-National Measure of Fear-Based Xenophobia: Development of a Cumulative Scale

To apply a Mokken Scale Procedure in developing a hierarchical cross-national scale to measure xenophobia, a pool of 30 xenophobia-related items was collected from several sources and modified using established unidimensional criteria. The survey was administered to 608 undergraduate students in the USA, 193 undergraduate students in The Netherlands, and 303 undergraduate students in Norway. 14 items measuring perceived threat or fear and meeting the criteria of the Stereotype Content Model were selected for further analysis. A separate item analysis and, subsequently, Mokken Scale Procedure yielded a cumulative scale with the same five items for each of the three samples. The items and the total scale met criteria for homogeneity in all samples with H >…. 40.
Multiple 3D Object tracking for augmented reality

We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real-time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: Frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches, and demonstrate our method on several real sequences.
Cell adhesion molecules in the CNS

Cell-cell adhesions are important for brain morphology and highly coordinated brain functions such as memory and learning ([Sanes and Yamagata, 1999][1]; [Yamagata et al., 2003][2]; [Washbourne et al., 2004][3]). During early development of the nervous system, neurons elongate their axons towards
Accuracy of the SpaceLabs 90207 determined by the British Hypertension Society protocol.

Results: The three recorders passed the before-use interdevice variability assessment, after which 84% of inflations recorded with these devices during the in-use phase gave valid readings, and the three devices subsequently passed the after-use interdevice variability assessment. The main validation test was carried out on one device in 86 subjects with a wide range of pressures, the results being analysed according to a grading system from A to D. The SpaceLabs 90207 acheived B rating for both systolic and diastolic pressures and also satisfied the criteria for accuracy of the Association for the Advancement of Medical lnstrumentation (AAMI), with an average difference (f s.d. 1 of 1 f 7 and 3 f 6 mmHg for systolic and diastolic pressure, respectively. Subject acceptability was good. The manufacturer's manual was satisfactory overall, but contained a number of errors and omissions.
Hide and Seek : Detecting Hit Inflation Fraud in Streams of Web Advertising Networks

As the Internet continues to grow, the Internet advertising industry flourishes as a means of reaching the appropriate market segments. Internet advertisers provide the monetary incentive for Internet publishers to display advertisements on their Web sites. Internet advertisers and publishers contract through a commissioner that takes care of the accounting issues, and earns a commission on the advertisers’ payments. Some publishers are dishonest, and use automation to generate traffic to defraud the advertisers. The commissioner, who is supposed to distinguish fraudulent traffic from normal traffic, cannot track individual computers in order not to violate surfers’ privacy. In this paper, we describe the advertising network model in detail, and share, with the research community, our field experience and concerns about detecting fraudulent publishers. This paper provides a classification of the publishers’ hit inflation techniques, and stream analysis schemes that would detect fraud attacks of many classes of the proposed classification. For some classes, we abstract detecting their fraud attacks as theoretical stream analysis problems that we propose as open problems. In addition, we consider the problem of detecting automated activities. A framework is outlined for deploying the proposed fraud detection algorithms on a generic architecture. We conclude by some findings of our attempt to detect fraud on a real network.
Synthesis and electrochemical applications of boron- and phosphorus-doped carbon nanotubes

The catalytic chemical vapor deposition method was applied for the synthesis of B-MWCNTs and P-MWCNTs. P-MWCNTs and B-MWCNTs with different structures, namely vertically aligned, hollow vertically aligned, Y-shaped and horizontally oriented nanotubes were produced by using different doping and carbon source materials. The B-MWCNTs and P-MWCNTs were characterized using Raman spectroscopy, scanning electron microscopy, transmission electron microscopy in combination with electron energy loss spectroscopy and X-ray photo electron spectroscopy. The B-MWCNTs and P-MWCNTs were electrochemically studied by using either [Fe(CN)6]^3-/4- redox system in KCl solution or dopamine/dopamine quinone redox system in phosphate buffer solution (pH=7) by means of cyclic voltammetry and electrochemical impedance spectroscopy. The effects of surface functionalisation with AuNPs, oxidation with piranha solution, and acid treatment with HCl on the electrochemical response of B-MWCNTs and P-MWCNTs towards [Fe(CN)6]^3-/4- and dopamine/dopamine quinone were also studied. The results demonstrated that the electrochemical behaviour of B-MWCNTs and P-MWCNTs is strongly influenced by the nanotubes structure and configuration (sole nanotube or cluster nanotubes) as well as by the presence of reaction by-product on the nanotube surface such as carbon cluster and onion-like carbon. Y-shaped B-MWCNTs show faster electron transfer compared to either vertically aligned B-MWCNTs or P-MWCNTs with nanographitic carbon cluster. The kinetic for electron transfer on Y-shaped B-MWCNTs and P-MWCNTs with nanographitic carbon cluster enhances upon AuNPs functionalisation.
Weakly Supervised Learning in Deformable EM Image Registration Using Slice Interpolation

Alignment of large-scale serial-section electron microscopy (ssEM) images is crucial for successful analysis in nano-scale connectomics. Despite various image registration algorithms proposed in the past, large-scale ssEM alignment remains challenging due to the size and complex nature of the data. Recently, the application of unsupervised machine learning in medical image registration has shown promise in efforts to replace an expensive numerical computation process with a once-deployed feed-forward neural network. However, the anisotropy in most ssEM data makes it difficult to directly adopt such learning-based methods for the registration of these images. Here, we propose a novel deformable image registration approach based on weakly supervised learning that can be applied to registering ssEM images at scale. The proposed method leverages slice interpolation to improve registration between images with sudden and large structural changes. In addition, the proposed method only requires roughly aligned data for training the interpolation network while the deformation network can be trained in an unsupervised fashion. We demonstrate the efficacy of the method on real ssEM datasets.
Equivalence of synthesis and atomic formulations of sparse recovery

Recovery of sparse signals from linear, dimensionality reducing measurements broadly falls under two well-known formulations, named the synthesis and the analysis formulations. Recently, Chandrasekaran et al. introduced a new algorithmic sparse recovery framework based on the convex geometry of linear inverse problems, called the atomic norm formulation. In this paper, we prove that atomic norm formulation and synthesis formulation are equivalent for closed atomic sets. Hence, it is possible to use the synthesis formulation in order to obtain the so-called atomic decompositions of signals. In order to numerically observe this equivalence we derive exact linear matrix inequality representations, also known as the theta bodies, of the centrosymmertic polytopes formed from the columns of the simplex and their antipodes. We then illustrate that the atomic and synthesis recovery results agree on machine precision on randomly generated sparse recovery problems.
Development of K500 Signal Processing System using Raspberry PI in the 3-electrodes Electrochemical Sensor

The electrochemical sensor exploits current or voltage on the electrodes when the chemical reaction occurs between the sensitive part of the electrode and the heavy metal ion detected. The output of current or voltage changes corresponds to the amount of ion concentration of heavy metal in water. This research aims to develop signal processing system using raspberry PI as a supporting electronic scheme of electrochemical sensor to detect and analize heavy metal pollutant. The system contains of potentiostat, signal conditioning and data acquisition schemes. This research covers the activities of the design and development of Raspberry Pi based supporting electronic scheme, PCB and the electronic components, as well as the software program for the measurement of signal input from the electrochemical sensor. The performance of K500 system developed in the research is a little bit lower than that of the system published by another researcher. Despite its performance, this system costs only $45 cheaper than previous system that costs $100. For full version, i.e. including Raspberry Pi as a server, the K500 system with the dimension of 110x90x70 mm costs only $70, cheaper than the other system using laptop computer as a server that costs $60 without its server.
Retargeting Without Tracking

Retargeting ads are increasingly prevalent on the Internet as their effectiveness has been shown to outperform conventional targeted ads. Retargeting ads are not only based on users' interests, but also on their intents, i.e. commercial products users have shown interest in. Existing retargeting systems heavily rely on tracking, as retargeting companies need to know not only the websites a user has visited but also the exact products on these sites. They are therefore very intrusive, and privacy threatening. Furthermore, these schemes are still sub-optimal since tracking is partial, and they often deliver ads that are obsolete (because, for example, the targeted user has already bought the advertised product). This paper presents the first privacy-preserving retargeting ads system. In the proposed scheme, the retargeting algorithm is distributed between the user and the advertiser such that no systematic tracking is necessary, more control and transparency is provided to users, but still a lot of targeting flexibility is provided to advertisers. We show that our scheme, that relies on homomorphic encryption, can be efficiently implemented and trivially solves many problems of existing schemes, such as frequency capping and ads freshness.
A Swiss neighbourhood index of socioeconomic position: development and association with mortality

Background Area-based measures of socioeconomic position (SEP) suitable for epidemiological research are lacking in Switzerland. The authors developed the Swiss neighbourhood index of SEP (Swiss-SEP). Methods Neighbourhoods of 50 households with overlapping boundaries were defined using Census 2000 and road network data. Median rent per square metre, proportion households headed by a person with primary education or less, proportion headed by a person in manual or unskilled occupation and the mean number of persons per room were analysed in principle component analysis. The authors compared the index with independent income data and examined associations with mortality from 2001 to 2008. Results 1.27 million overlapping neighbourhoods were defined. Education, occupation and housing variables had loadings of 0.578, 0.570 and 0.362, respectively, and median rent had a loading of −0.459. Mean yearly equivalised income of households increased from SFr42 000 to SFr72 000 between deciles of neighbourhoods with lowest and highest SEP. Comparing deciles of neighbourhoods with lowest to highest SEP, the age- and sex-adjusted HR was 1.38 (95% CI 1.36 to 1.41) for all-cause mortality, 1.83 (95% CI 1.71 to 1.95) for lung cancer, 1.48 (95% CI 1.44 to 1.51) for cardiovascular diseases, 2.42 (95% CI 1.94 to 3.01) for traffic accidents, 0.93 (95% CI 0.85 to 1.02) for breast cancer and 0.86 (95% CI 0.78 to 0.95) for suicide. Conclusions Developed using a novel approach to define neighbourhoods, the Swiss-SEP index was strongly associated with household income and some causes of death. It will be useful for clinical- and population-based studies, where individual-level socioeconomic data are often missing, and to investigate the effects on health of the socioeconomic characteristics of a place.
A middleware service for coordinated adaptation of communication services in groups of devices

Recent research in pervasive computing has shown that context-awareness and dynamic adaptation are fundamental requirements of mobile distributed applications. However, most approaches that focus on context-aware dynamic adaptation use only the context information available at the mobile device to trigger a local adaptation. However, for distributed collaborative applications this is clearly insufficient, since a same adaptation has to be done, in synch, at all mobile devices of the group, and hence should also be based on a commonly agreed context. Therefore, for such kinds of applications one requires mechanisms and protocols to exchange the context information among the devices and to coordinate of the adaptation operations at a group of mobile device. In this paper we present a middleware service for coordinated adaptation of communication services in groups of devices. At each device this adaptation is achieved with minimal disruption for the application's remote interactions. This middleware service is based on the notion of global context and a generic protocol for global context election and synchronization of the adaptation steps, which we called Moratus. Our middleware service was implemented using JGroups and evaluated for groups of up to 30 devices, showing acceptable latency for groups of such size.
Solubility of Carbon Dioxide in Aqueous N-methyldiethanolamine

In this chapter the electrolyte equation of state proposed by Solbraa (E. Solbraa, Ph.D. thesis Norwegian University of Science and Technology (2002)) is studied and improved to describe the solubility of carbon dioxide in aqueous solutions of Nmethyldiethanolamine quantitatively. In this equation both the vapor and the liquid are described by an equation of state. The molecular part of the equation is based on Schwarzentruber’s modification of the Redlich-Kwong equation of state (J. Scharzentruber, H. Renon, S. Watanasiri, Fluid Phase Eq., 52 (1989) 127-134) with the Huron-Vidal mixing rule (M.J. Huron, J. Vidal, Fluid Phase Eq., 3 (1979) 255271). Three ionic terms are added to this equation – a short-range ionic term, a long-range ionic term (MSA) and a Born term. The thermodynamic model has the advantage that it reduces to a standard cubic equation of state if no ions are present in the solution, and that publicly available interaction parameters used in the Huron-Vidal mixing rule can be utilized. In this chapter binary molecular and ionic interaction parameters are studied and optimized. With the updated model it is