"Where we can go?": Indonesia's struggle against unemployment and man-power export phenomenon.

"More than 10,5 million Indonesians are seeking work. Neither under-qualification for labour nor discouragement is to blame for this high unemployment, but rather the low productive investment rate and unhealthy investment climate. Facing the 9.75% unemployment rate and increasing poverty, Indonesia's government has tried to develop the potential of TKI (Indonesian Migrant Worker) programme seriously since 2004. TKI programme contributes around half a million occupations per year. Indonesian government registered a substantial rate of foreign income from this sector. Yet behind these nice figures, migrant workers have to face numerous problems and - in many cases - abuse. In 2002 alone, there were at least 1.3 million cases of migrant workers, e.g. death (by falling from buildings), sexual harassment/ abuse, confinement, extortion, document fraud, underpayment/ unpaid wages and illegal placement. Human trafficking has been also found amongst illegal placement of migrant workers. Most victims are women and children. Indonesian government has tried several policies to improve the protection of migrant workers and to simplify the placement procedures. Illegal and criminal brokerage as well as insufficient bilateral agreements with employer countries are identified as major problems." (author's abstract

Collapse of Flexible Polyelectrolytes in Multivalent Salt Solutions

The collapse of flexible polyelectrolytes in a solution of multivalent counterions is studied by means of a two state model. The states correspond to rod-like and spherically collapsed conformations respectively. We focus on the very dilute monomer concentration regime where the collapse transition is found to occur when the charge of the multivalent salt is comparable (but smaller) to that of the monomers. The main contribution to the free energy of the collapsed conformation is linear in the number of monomers $N$, since the internal state of the collapsed polymer approaches that of an amorphous ionic solid. The free energy of the rod-like state grows as $N\ln N$, due to the electrostatic energy associated with that shape. We show that practically all multivalent counterions added to the system are condensed into the polymer chain, even before the collapse.Comment: LaTeX-revtex, psfig file, 4 figure

The Entelechial Thinker in Space: ‘Worlds within Worlds’ in Durrell, Flaubert, and Carroll

This thesis argues that the interior space of each individual mind has infinite potentiality to do or create x new reality in one’s life via possible worlds. I use Lawrence Durrell’s short story “Zero” (1939), Gustave Flaubert’s “Un coeur simple” (1877), and Lewis Carroll’s Alice’s Adventures in Wonderland (1865) as literary representations of how readers outside of the literary text share an unbreakable bond with universal space. I discuss the infinite potentiality of the finite being, and the experiential data in the process of entelechy, or epistemological maturation of the mind. I bring Leibniz’s theory of the continuum of infinitesimals and Henri Bergson’s metaphysics of duration and consciousness into the argument to advance the premise that the only limiting factor on the mind’s ability to shape its own actual world environment via possible-world ideation is the mind itself

DeepRICH: Learning Deeply Cherenkov Detectors

Imaging Cherenkov detectors are largely used for particle identification (PID) in nuclear and particle physics experiments, where developing fast reconstruction algorithms is becoming of paramount importance to allow for near real time calibration and data quality control, as well as to speed up offline analysis of large amount of data. In this paper we present DeepRICH, a novel deep learning algorithm for fast reconstruction which can be applied to different imaging Cherenkov detectors. The core of our architecture is a generative model which leverages on a custom Variational Auto-encoder (VAE) combined to Maximum Mean Discrepancy (MMD), with a Convolutional Neural Network (CNN) extracting features from the space of the latent variables for classification. A thorough comparison with the simulation/reconstruction package FastDIRC is discussed in the text. DeepRICH has the advantage to bypass low-level details needed to build a likelihood, allowing for a sensitive improvement in computation time at potentially the same reconstruction performance of other established reconstruction algorithms. In the conclusions, we address the implications and potentialities of this work, discussing possible future extensions and generalization.Comment: 14 pages, 9 figures, preprin

Pixle: a fast and effective black-box attack based on rearranging pixels

Recent research has found that neural networks are vulnerable to several types of adversarial attacks, where the input samples are modified in such a way that the model produces a wrong prediction that misclassifies the adversarial sample. In this paper we focus on black-box adversarial attacks, that can be performed without knowing the inner structure of the attacked model, nor the training procedure, and we propose a novel attack that is capable of correctly attacking a high percentage of samples by rearranging a small number of pixels within the attacked image. We demonstrate that our attack works on a large number of datasets and models, that it requires a small number of iterations, and that the distance between the original sample and the adversarial one is negligible to the human eye

Continual Learning with Invertible Generative Models

Catastrophic forgetting (CF) happens whenever a neural network overwrites past knowledge while being trained on new tasks. Common techniques to handle CF include regularization of the weights (using, e.g., their importance on past tasks), and rehearsal strategies, where the network is constantly re-trained on past data. Generative models have also been applied for the latter, in order to have endless sources of data. In this paper, we propose a novel method that combines the strengths of regularization and generative-based rehearsal approaches. Our generative model consists of a normalizing flow (NF), a probabilistic and invertible neural network, trained on the internal embeddings of the network. By keeping a single NF throughout the training process, we show that our memory overhead remains constant. In addition, exploiting the invertibility of the NF, we propose a simple approach to regularize the network's embeddings with respect to past tasks. We show that our method performs favorably with respect to state-of-the-art approaches in the literature, with bounded computational power and memory overheads.Comment: arXiv admin note: substantial text overlap with arXiv:2007.0244

The cytochrome c gene proximal enhancer drives activity-dependent reporter gene expression in hippocampal neurons

The proximal enhancer of the cytochrome c gene (Cycs) contains binding sites for both cAMP response element binding proteins (CREB) and Nuclear Respiratory Factor 1 (NRF1). To investigate how neuronal activity regulates this enhancer region, a lentivirus was constructed in which a short-lived green fluorescent protein (GFP) was placed under the transcriptional control of the Cycs proximal enhancer linked to a synthetic core promoter. Primary hippocampal neurons were infected, and the synaptic strengths of individual neurons were measured by whole-cell patch clamping. On average the amplitude of miniature postsynaptic currents (mEPSCs) was higher in brighter GFP+ neurons, while the frequency of mEPSCs was not significantly different. Increasing neural activity by applying a GABAA receptor antagonist increased GFP expression in most neurons, which persisted after homeostatic synaptic scaling as evidenced by a decrease in the amplitude and frequency of mEPSCs. Removing the CREB binding sites revealed that calcium influx through L-type channels and NMDA receptors, and ERK1/2 activation played a role in NRF1-mediated transcription. CREB and NRF1, therefore, combine to regulate transcription of Cycs in response to changing neural activity