Kondo Effect in Fermi Systems with a Gap: A Renormalization Group Study

We present the results of a Wilson Renormalization Group study of the single-impurity Kondo and Anderson models in a system with a gap in the conduction electron spectrum. The behavior of the impurity susceptibility and the zero-frequency response function, $T>$ are discussed in the cases with and without particle-hole symmetry. In addition, for the asymmetric Anderson model the correlation functions, $<\vec S \cdot\vec \sigma (0)>$,$$, and$$ are computed.Comment: 10 pages, 10 figure

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose.

The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrient Database, both of which require a license. Manual lookup of ASA24 foods into NDSR is time-consuming but currently the only way to acquire NCC-exclusive nutrients. Using lactose as an example, we evaluated machine learning and database matching methods to estimate this NCC-exclusive nutrient from ASA24 reports. ASA24-reported foods were manually looked up into NDSR to obtain lactose estimates and split into training (n = 378) and test (n = 189) datasets. Nine machine learning models were developed to predict lactose from the nutrients common between ASA24 and the NCC database. Database matching algorithms were developed to match NCC foods to an ASA24 food using only nutrients ("Nutrient-Only") or the nutrient and food descriptions ("Nutrient + Text"). For both methods, the lactose values were compared to the manual curation. Among machine learning models, the XGB-Regressor model performed best on held-out test data (R2 = 0.33). For the database matching method, Nutrient + Text matching yielded the best lactose estimates (R2 = 0.76), a vast improvement over the status quo of no estimate. These results suggest that computational methods can successfully estimate an NCC-exclusive nutrient for foods reported in ASA24

The aspartic proteinase family of three Phytophthora species

Background: Phytophthora species are oomycete plant pathogens with such major social and economic impact that genome sequences have been determined for Phytophthora infestans, P. sojae and P. ramorum. Pepsin-like aspartic proteinases (APs) are produced in a wide variety of species (from bacteria to humans) and contain conserved motifs and landmark residues. APs fulfil critical roles in infectious organisms and their host cells. Annotation of Phytophthora APs would provide invaluable information for studies into their roles in the physiology of Phytophthora species and interactions with their hosts. Results: Genomes of Phytophthora infestans, P. sojae and P. ramorum contain 11-12 genes encoding APs. Nine of the original gene models in the P. infestans database and several in P. sojae and P. ramorum (three and four, respectively) were erroneous. Gene models were corrected on the basis of EST data, consistent positioning of introns between orthologues and conservation of hallmark motifs. Phylogenetic analysis resolved the Phytophthora APs into 5 clades. Of the 12 sub-families, several contained an unconventional architecture, as they either lacked a signal peptide or a propart region. Remarkably, almost all APs are predicted to be membrane-bound. Conclusions: One of the twelve Phytophthora APs is an unprecedented fusion protein with a putative G-protein coupled receptor as the C-terminal partner. The others appear to be related to well-documented enzymes from other species, including a vacuolar enzyme that is encoded in every fungal genome sequenced to date. Unexpectedly, however, the oomycetes were found to have both active and probably-inactive forms of an AP similar to vertebrate BACE, the enzyme responsible for initiating the processing cascade that generates the Aβ peptide central to Alzheimer's Disease. The oomycetes also encode enzymes similar to plasmepsin V, a membrane-bound AP that cleaves effector proteins of the malaria parasite Plasmodium falciparum during their translocation into the host red blood cell. Since the translocation of Phytophthora effector proteins is currently a topic of intense research activity, the identification in Phytophthora of potential functional homologues of plasmepsin V would appear worthy of investigation. Indeed, elucidation of the physiological roles of the APs identified here offers areas for future study. The significant revision of gene models and detailed annotation presented here should significantly facilitate experimental design.Fil: Kay, John. Cardiff University; Reino UnidoFil: Meijer, Harold J. G.. Wageningen University; Reino UnidoFil: Ten Have, Arjen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigaciones Biológicas; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: van Kan, Jan A. L.. Wageningen University; Reino Unid

Optics-less smart sensors and a possible mechanism of cutaneous vision in nature

Optics-less cutaneous (skin) vision is not rare among living organisms, though its mechanisms and capabilities have not been thoroughly investigated. This paper demonstrates, using methods from statistical parameter estimation theory and numerical simulations, that an array of bare sensors with a natural cosine-law angular sensitivity arranged on a flat or curved surface has the ability to perform imaging tasks without any optics at all. The working principle of this type of optics-less sensor and the model developed here for determining sensor performance may be used to shed light upon possible mechanisms and capabilities of cutaneous vision in nature

Electronic and Magnetic Properties of Partially-Open Carbon Nanotubes

On the basis of the spin-polarized density functional theory calculations, we demonstrate that partially-open carbon nanotubes (CNTs) observed in recent experiments have rich electronic and magnetic properties which depend on the degree of the opening. A partially-open armchair CNT is converted from a metal to a semiconductor, and then to a spin-polarized semiconductor by increasing the length of the opening on the wall. Spin-polarized states become increasingly more stable than nonmagnetic states as the length of the opening is further increased. In addition, external electric fields or chemical modifications are usable to control the electronic and magnetic properties of the system. We show that half-metallicity may be achieved and the spin current may be controlled by external electric fields or by asymmetric functionalization of the edges of the opening. Our findings suggest that partially-open CNTs may offer unique opportunities for the future development of nanoscale electronics and spintronics.Comment: 6 figures, to appear in J. Am. Chem. So

Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors

Concept drift is a major challenge faced by machine learning-based malware detectors when deployed in practice. While existing works have investigated methods to detect concept drift, it is not yet well understood regarding the main causes behind the drift. In this paper, we design experiments to empirically analyze the impact of feature-space drift (new features introduced by new samples) and compare it with data-space drift (data distribution shift over existing features). Surprisingly, we find that data-space drift is the dominating contributor to the model degradation over time while feature-space drift has little to no impact. This is consistently observed over both Android and PE malware detectors, with different feature types and feature engineering methods, across different settings. We further validate this observation with recent online learning based malware detectors that incrementally update the feature space. Our result indicates the possibility of handling concept drift without frequent feature updating, and we further discuss the open questions for future research

Coexistence of antiferromagnetic order and unconventional superconductivity in heavy fermion compounds CeRh_{1-x}Ir_xIn_5: nuclear quadrupole resonance studies

We present a systematic ^{115}In NQR study on the heavy fermion compounds CeRh_{1-x}Ir_xIn_5 (x=0.25, 0.35, 0.45, 0.5, 0.55 and 0.75). The results provide strong evidence for the microscopic coexistence of antiferromagnetic (AF) order and superconductivity (SC) in the range of 0.35 \leq x \leq 0.55. Specifically, for x=0.5, T_N is observed at 3 K with a subsequent onset of superconductivity at T_c=0.9 K. T_c reaches a maximum (0.94 K) at x=0.45 where T_N is found to be the highest (4.0 K). Detailed analysis of the measured spectra indicate that the same electrons participate in both SC and AF order. The nuclear spin-lattice relaxation rate 1/T_1 shows a broad peak at T_N and follows a T^3 variation below T_c, the latter property indicating unconventional SC as in CeIrIn_5 (T_c=0.4 K). We further find that, in the coexistence region, the T^3 dependence of 1/T_1 is replaced by a T-linear variation below T\sim 0.4 K, with the value \frac{(T_1)_{T_c}}{(T_1)_{low-T}} increasing with decreasing x, likely due to low-lying magnetic excitations associated with the coexisting magnetism.Comment: 20 pages, 14 figure

Search in weighted complex networks

We study trade-offs presented by local search algorithms in complex networks which are heterogeneous in edge weights and node degree. We show that search based on a network measure, local betweenness centrality (LBC), utilizes the heterogeneity of both node degrees and edge weights to perform the best in scale-free weighted networks. The search based on LBC is universal and performs well in a large class of complex networks.Comment: 14 pages, 5 figures, 4 tables, minor changes, added a referenc