Predictors of HIV self-testing among health workers at Nyeri Provincial Hospital in Kenya

Background: HIV self-testing is recognised as a possible option of expanding access to HIV testing and counselling (HTC). There is high demand for self testing among health workers. However, in many health facilities in Kenya, the rate of unregulated self-testing and factors influencing the practice remain unknown.Objectives: To determine the prevalence and factors influencing HIV self-testing among health workersDesign: A descriptive cross-sectional study.Setting: Nyeri Provincial Hospital, the largest public hospital in Central Kenya.Subjects: Four hundred and fourteen Health workers at Nyeri Provincial Hospital who included the following cadres: Nurses, Doctors, Clinical officers, Laboratory Technicians, Community Health Workers and HTC counsellors.Results: The proportion of self-testers were 65.8% (N=348). The significant predictors of HIV self-testing were identified as age, difficulty of conducting HIV self-test, reliability of HIV self-test results and confidence in HIV positive self-test results. Self-testers (n=229) identified factors that influenced them to self-test as: easy access to test kits, obligation to test themselves, saves time and fear of stigma. Non self-testers (n=119) identified inability to handle HIV positive results; idea of self-test scares me, fear of stigma and lack of access to test kits as factors inhibiting self-testing.Conclusions: Self-testing is highly practiced by health workers at Nyeri provincial hospital. HIV related stigma needs to be addressed. Increasing access to test kits may increase self-testing

Precedence-constrained scheduling problems parameterized by partial order width

Negatively answering a question posed by Mnich and Wiese (Math. Program. 154(1-2):533-562), we show that P2|prec,$p_j{\in}\{1,2\}$|$C_{\max}$, the problem of finding a non-preemptive minimum-makespan schedule for precedence-constrained jobs of lengths 1 and 2 on two parallel identical machines, is W[2]-hard parameterized by the width of the partial order giving the precedence constraints. To this end, we show that Shuffle Product, the problem of deciding whether a given word can be obtained by interleaving the letters of $k$ other given words, is W[2]-hard parameterized by $k$, thus additionally answering a question posed by Rizzi and Vialette (CSR 2013). Finally, refining a geometric algorithm due to Servakh (Diskretn. Anal. Issled. Oper. 7(1):75-82), we show that the more general Resource-Constrained Project Scheduling problem is fixed-parameter tractable parameterized by the partial order width combined with the maximum allowed difference between the earliest possible and factual starting time of a job.Comment: 14 pages plus appendi

Composite Fermion Metals from Dyon Black Holes and S-Duality

We propose that string theory in the background of dyon black holes in four-dimensional anti-de Sitter spacetime is holographic dual to conformally invariant composite Dirac fermion metal. By utilizing S-duality map, we show that thermodynamic and transport properties of the black hole match with those of composite fermion metal, exhibiting Fermi liquid-like. Built upon Dirac-Schwinger-Zwanziger quantization condition, we argue that turning on magnetic charges to electric black hole along the orbit of Gamma(2) subgroup of SL(2,Z) is equivalent to attaching even unit of statistical flux quanta to constituent fermions. Being at metallic point, the statistical magnetic flux is interlocked to the background magnetic field. We find supporting evidences for proposed holographic duality from study of internal energy of black hole and probe bulk fermion motion in black hole background. They show good agreement with ground-state energy of composite fermion metal in Thomas-Fermi approximation and cyclotron motion of a constituent or composite fermion excitation near Fermi-point.Comment: 30 pages, v2. 1 figure added, minor typos corrected; v3. revised version to be published in JHE

Simultaneous Neural Spike Encoding and Decoding Based on Cross-modal Dual Deep Generative Model

Neural encoding and decoding of retinal ganglion cells (RGCs) have been attached great importance in the research work of brain-machine interfaces. Much effort has been invested to mimic RGC and get insight into RGC signals to reconstruct stimuli. However, there remain two challenges. On the one hand, complex nonlinear processes in retinal neural circuits hinder encoding models from enhancing their ability to fit the natural stimuli and modelling RGCs accurately. On the other hand, current research of the decoding process is separate from that of the encoding process, in which the liaison of mutual promotion between them is neglected. In order to alleviate the above problems, we propose a cross-modal dual deep generative model (CDDG) in this paper. CDDG treats the RGC spike signals and the stimuli as two modalities, which learns a shared latent representation for the concatenated modality and two modal-specific latent representations. Then, it imposes distribution consistency restriction on different latent space, cross-consistency and cycle-consistency constraints on the generated variables. Thus, our model ensures cross-modal generation from RGC spike signals to stimuli and vice versa. In our framework, the generation from stimuli to RGC spike signals is equivalent to neural encoding while the inverse process is equivalent to neural decoding. Hence, the proposed method integrates neural encoding and decoding and exploits the reciprocity between them. The experimental results demonstrate that our proposed method can achieve excellent encoding and decoding performance compared with the state-of-the-art methods on three salamander RGC spike datasets with natural stimuli

Neural Encoding and Decoding with a Flow-based Invertible Generative Model

Recent studies on visual neural encoding and decoding have made significant progress, benefiting from the latest advances in deep neural networks having powerful representations. However, two challenges remain. First, the current decoding algorithms based on deep generative models always struggle with information losses, which may cause blurry reconstruction. Second, most studies model the neural encoding and decoding processes separately, neglecting the inherent dual relationship between the two tasks. In this paper, we propose a novel neural encoding and decoding method with a two-stage flow-based invertible generative model to tackle the above issues. First, a convolutional auto-encoder is trained to bridge the stimuli space and the feature space. Second, an adversarial cross-modal normalizing flow is trained to build up a bijective transformation between image features and neural signals, with local and global constraints imposed on the latent space to render cross-modal alignment. The method eventually achieves bi-directional generation of visual stimuli and neural responses with a combination of the flow-based generator and the auto-encoder. The flow-based invertible generative model can minimize information losses and unify neural encoding and decoding into a single framework. Experimental results on different neural signals containing spike signals and functional magnetic resonance imaging demonstrate that our model achieves the best comprehensive performance among the comparison models

First direct observation of Dirac fermions in graphite

Originating from relativistic quantum field theory, Dirac fermions have been recently applied to study various peculiar phenomena in condensed matter physics, including the novel quantum Hall effect in graphene, magnetic field driven metal-insulator-like transition in graphite, superfluid in 3He, and the exotic pseudogap phase of high temperature superconductors. Although Dirac fermions are proposed to play a key role in these systems, so far direct experimental evidence of Dirac fermions has been limited. Here we report the first direct observation of massless Dirac fermions with linear dispersion near the Brillouin zone (BZ) corner H in graphite, coexisting with quasiparticles with parabolic dispersion near another BZ corner K. In addition, we report a large electron pocket which we attribute to defect-induced localized states. Thus, graphite presents a novel system where massless Dirac fermions, quasiparticles with finite effective mass, and defect states all contribute to the low energy electronic dynamics.Comment: Nature Physics, in pres

Multicomponent fractional quantum Hall effect in graphene

We report observation of the fractional quantum Hall effect (FQHE) in high mobility multi-terminal graphene devices, fabricated on a single crystal boron nitride substrate. We observe an unexpected hierarchy in the emergent FQHE states that may be explained by strongly interacting composite Fermions with full SU(4) symmetric underlying degrees of freedom. The FQHE gaps are measured from temperature dependent transport to be up 10 times larger than in any other semiconductor system. The remarkable strength and unusual hierarcy of the FQHE described here provides a unique opportunity to probe correlated behavior in the presence of expanded quantum degrees of freedom.Comment: 5 pages, 3 figure

The nature of localization in graphene under quantum Hall conditions

Particle localization is an essential ingredient in quantum Hall physics [1,2]. In conventional high mobility two-dimensional electron systems Coulomb interactions were shown to compete with disorder and to play a central role in particle localization [3]. Here we address the nature of localization in graphene where the carrier mobility, quantifying the disorder, is two to four orders of magnitude smaller [4,5,6,7,8,9,10]. We image the electronic density of states and the localized state spectrum of a graphene flake in the quantum Hall regime with a scanning single electron transistor [11]. Our microscopic approach provides direct insight into the nature of localization. Surprisingly, despite strong disorder, our findings indicate that localization in graphene is not dominated by single particle physics, but rather by a competition between the underlying disorder potential and the repulsive Coulomb interaction responsible for screening.Comment: 18 pages, including 5 figure