N=1 Supersymmetric Yang-Mills on the lattice at strong coupling

We study N=1 supersymmetric SU(N) Yang-Mills theory on the lattice at strong coupling. Our method is based on the hopping parameter expansion in terms of random walks, resummed for any value of the Wilson parameter r in the small hopping parameter region. Results are given for the mesonic (2-gluino) and fermionic (3-gluino) propagators and spectrum.Comment: Latex file. 43 pages. Minor additional comments, references added, typos corrected. Accepted for publication in Int. J. Mod. Phys.

Recent results on self-dual configurations on the torus

We review the recent progress on our understanding of self-dual SU(N) Yang-Mills configurations on the torus.Comment: Latex 3 pages, 1 figure. Contribution to the Lat99 Proceeding

Perturbative construction of self-dual configurations on the torus

We develop a perturbative expansion which allows the construction of non-abelian self-dual SU(2) Yang-Mills field configurations on the four-dimensional torus with topological charge 1/2. The expansion is performed around the constant field strength abelian solutions found by 't Hooft. Next to leading order calculations are compared with numerical results obtained with lattice gauge theory techniques.Comment: latex file. 32 pages and 4 figures(24 eps files

Evaluating the effect of age and area of residence in the metal and metalloid contents in human hair and urban topsoils

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Monitoring the levels of trace elements in hair can allow estimating the effects of the geographical location and also can provide a notion of the metal body burden. However, the use of human hair is controversial due to the different confounding factors that could affect the presence of trace elements in hair. As a result, a comprehensive monitoring study was performed in Alcalá de Henares, one of the major cities in the Madrid region, Spain. Trace elements have been monitored in urban topsoils and in human hair of two well-defined and healthy groups of population: children (6–9 years) and adolescents (13–16 years). The city was divided into four areas or zones with different characteristics to assess the possible effect of area of residence and age in the presence of Al, As, Be, Cd, Cr, Cu, Hg, Mn, Pb, Sn, Ti, Tl and Zn in soils and hair. There is no current hypothesis that explains the possible effect of the area of monitoring in the distribution of Be, Cr, Ni, Sn and Ti found in these urban soils, maybe because urban soils receive high disturbance, and there are many factors involved. The presence of most of the trace elements monitored was significantly higher in the hair of the children population, except for Sn and Zn. This could be attributed mainly to dietary habits. Other factors influencing metal content in hair such as environmental factors would have had a minimal effect in the population groups here studied. Finally, none of the levels of trace elements studied in hair were significantly correlated with levels measured in the topsoils of public parks in Alcalá de Henares, with the exception of Pb in adolescent participants

Real-Time Road Hazard Information System

Infrastructure is a significant factor in economic growth for systems of government. In order to increase economic productivity, maintaining infrastructure quality is essential. One of the elements of infrastructure is roads. Roads are means which help local and national economies be more productive. Furthermore, road damage such as potholes, debris, or cracks is the cause of many on-road accidents that have cost the lives of many drivers. In this paper, we propose a system that uses Convolutional Neural Networks to detect road degradations without data pre-processing. We utilize the state-of-the-art object detection algorithm, YOLO detector for the system. First, we developed a basic system working on data collecting, pre-processing, and classification. Secondly, we improved the classification performance achieving 97.98% in the overall model testing, and then we utilized pixel-level classification and detection with a method called semantic segmentation. We were able to achieve decent results using this method to detect and classify four different classes (Manhole, Pothole, Blurred Crosswalk, Blurred Street Line). We trained a segmentation model that recognizes the four classes mentioned above and achieved great results with this model allowing the machine to effectively and correctly identify and classify our four classes in an image. Although we obtained excellent accuracy from the detectors, these do not perform particularly well on embedded systems due to their network size. Therefore, we opted for a smaller, less accurate detector that will run in real time on a cheap embedded system, like the Google Coral Dev Board, without needing a powerful and expensive GPU

Structural Variations Induced by Temperature Changes in Rotavirus VP6 Protein Immersed in an Electric Field and Their Effects on Epitopes of The Region 300-396

Rotavirus diarrhea is an infectious intestinal disease that causes about 215 thousand deaths annually in infants under five years old. This virus is formed by three layers of concentric proteins that envelop its genome, from which VP6 structural protein is the most conserved among rotavirus serotypes and an excellent vaccine candidate. Recent studies have shown that structural proteins are susceptible to losing their biological function when their conformation is modified by moderate temperature increments, and in the case of VP6, its antigen efficiency decreases. We performed an in silicoanalysis to identify the structural variations in the epitopes 301-315, 357-366, and 376-384 of the rotavirus VP6 protein -in a hydrated medium- when the temperature is increased from 310 K to 322 K. In the latter state, we applied an electric field equivalent to a low energy laser pulse and calculated the fluctuations per amino acid residue. We identified that the region 301-315 has greater flexibility and density of negative electrical charge; nevertheless, at 322 K it experiences a sudden change of secondary structure that could decrease its efficiency as an antigenic determinant. The applied electric field induces electrical neutrality in the region 357-366, whereas in 376-384 inverts the charge, implying that temperature changes in the range 310 K-322 K are a factor that promotes thermoelectric effects in the VP6 protein epitopes in the region 300-396

Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection

In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1alpha + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFalpha (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine+IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFalpha in serum and [Fractalkine + IP-10 + IL-1alpha + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva

Role of voltage-gated proton channel (Hv1) in cancer biology

The acid-base characteristics of tumor cells and the other elements that compose the tumor microenvironment have been topics of scientific interest in oncological research. There is much evidence confirming that pH conditions are maintained by changes in the patterns of expression of certain proton transporters. In the past decade, the voltage-gated proton channel (Hv1) has been added to this list and is increasingly being recognized as a target with onco-therapeutic potential. The Hv1 channel is key to proton extrusion for maintaining a balanced cytosolic pH. This protein-channel is expressed in a myriad of tissues and cell lineages whose functions vary from producing bioluminescence in dinoflagellates to alkalizing spermatozoa cytoplasm for reproduction, and regulating the respiratory burst for immune system response. It is no wonder that in acidic environments such as the tumor microenvironment, an exacerbated expression and function of this channel has been reported. Indeed, multiple studies have revealed a strong relationship between pH balance, cancer development, and the overexpression of the Hv1 channel, being proposed as a marker for malignancy in cancer. In this review, we present data that supports the idea that the Hv1 channel plays a significant role in cancer by maintaining pH conditions that favor the development of malignancy features in solid tumor models. With the antecedents presented in this bibliographic report, we want to strengthen the idea that the Hv1 proton channel is an excellent therapeutic strategy to counter the development of solid tumors

Silicic Acid and Beer Consumption Reverses the Metal Imbalance and the Prooxidant Status Induced by Aluminum Nitrate in Mouse Brain

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Abstract: Background: Emerging evidence suggests that by affecting mineral balance, aluminum (Al) may enhance some events associated with neurodegenerative diseases. Aim: To examine the effect of Al(NO3)3 exposure on brain Al, cooper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), silicon (Si), and zinc (Zn) levels, and the metal-change implication in brain oxidant and inflammatory status. Methods: Four groups of six-week-old male NMRI mice were treated for three months: i) controls, administrated with deionized water; ii) Al, which received Al(NO3)3; iii) Al+silicic acid, which were given Al(NO3)3 plus silicic acid; and iv) Al+beer, which received Al(NO3)3 plus beer. Results: Brain Al and TBARS levels and TNFα and GPx expressions increased, while Cu, Mn, and Zn levels, and catalase and CuZn-SOD expression decreased (at least, p < 0.05) in Al versus control animals. Al, Si, and TBARS levels and TNFα expression decreased (p < 0.05) in Al+silicic acid and Al+beer specimens while Cu, Mn, and Zn levels and antioxidant expression increased versus the Al group. Brain Al levels correlated negatively with those of Cu, Fe, Mn, and Zn, and catalase, CuZn-SOD, and GPx enzyme expressions but positively with Si and TBARS levels and TNFα expression. Two components of the principal component analysis (PCA) explained 71.2% of total data variance (p < 0.001). PCA connected the pro-oxidant markers with brain Al content, while brain Zn and Cu levels were closer to antioxidant enzyme expression. Conclusion: Administration of Al(NO3)3 induced metal imbalance, inflammation, and antioxidant status impairment in the brain. Those effects were blocked to a significant extent by silicic acid and beer administration