Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy

Counterfactual explanations are an emerging tool to enhance interpretability of deep learning models. Given a sample, these methods seek to find and display to the user similar samples across the decision boundary. In this paper, we propose a generative adversarial counterfactual approach for satellite image time series in a multi-class setting for the land cover classification task. One of the distinctive features of the proposed approach is the lack of prior assumption on the targeted class for a given counterfactual explanation. This inherent flexibility allows for the discovery of interesting information on the relationship between land cover classes. The other feature consists of encouraging the counterfactual to differ from the original sample only in a small and compact temporal segment. These time-contiguous perturbations allow for a much sparser and, thus, interpretable solution. Furthermore, plausibility/realism of the generated counterfactual explanations is enforced via the proposed adversarial learning strategy

Algebraic properties of operator precedence languages

This paper presents new results on the algebraic ordering properties of operator precedence grammars and languages. This work was motivated by, and applied to, the mechanical acquisition or inference of operator precedence grammars. A new normal form of operator precedence grammars called homogeneous is defined. An algorithm is given to construct a grammar, called max-grammar, generating the largest language which is compatible with a given precedence matrix. Then the class of free grammars is introduced as a special subclass of operator precedence grammars. It is shown that operator precedence languages corresponding to a given precedence matrix form a Boolean algebra

CENTRE OF PRESSURE DURING COUNTERMOVEMENT JUMP: IS IT RELATED TO EXPERTISE OR PERFORMANCE?

The purpose of this study was to investigate how specific variables related to the centre of pressure (CoP) trajectory during a countermovement jump (CMJ) carry information related to expertise and performance. The variables investigated were: lengths and average velocities during eccentric (Ecc) and concentric (Con) phases, medio-lateral (ML) and antero-posterior (AP) ranges of movement, and ML bias. In terms of expertise, the curves were tracked and compared over four jump sessions conducted by both experienced and inexperienced jumpers to investigate adaptive changes towards a more efficient way of jumping. Links between performance and those characteristics were also investigated. Our study indicated that no useful information related to either expertise or performance can be extracted from the CoP trajectory during a CMJ

Implementasi Lean Manufacuring pada Proses Produksi untuk Mengurangi Pemborosan Persediaan

Penelitian ini dilakukan pada Perusahaan manufaktur sepatu bertaraf Internasional. Saat ini, terdapat penumpukan persediaan yang terjadi di setiap stasiun kerja. Penelitian ini mengidentifikasi alat yang tepat untuk memetakan secara detail aliran nilai (value stream), mengidentifikasi faktor penyebab terjadinya pemborosan, memberikan dan mengimplementasikan usulan tindakan perbaikan untuk meminimalkan pemborosan persediaan pada proses produksi. Mengacu pada pendekatan lean manufacturing, penelitian ini dimulai dengan memetakan aliran proses saat ini dengan menggunakan Value Stream Mapping (VSM). Tahap berikutnya, dilakukan identifikasi pemborosan dengan menggunakan Waste Assessment Model (WAM) dan menetapkan alat yang cocok untuk memetakan secara detail aliran nilai dengan menggunakan VALSAT. Selanjutnya, menganalisis penyebab dominan dari pemborosan persediaan dengan menggunakan fishbone diagram. Alat yang tepat untuk memetakan aliran nilai secara detail dengan menggunakan VALSAT adalah Process Activity Mapping (PAM) dengan total skor 500,12. Kemudian, faktor dominan yang menjadi penyebab terjadinya pemborosan persediaan disebabkan oleh 3 faktor yaitu manusia, metode, dan material. Tahap penyelesaian masalah dilakukan dengan merancang sistem kanban dan diimplementasikan ke value stream tersebut. Setelah mengimplementasikan usulan tindakan, diperoleh jumlah persediaan berkurang. Pada kondisi aktual sebelum diterapkan sistem kanban, jumlah persediaan tercatat 12.945 pasang. Setelah diterapkan sistem kanban, jumlah persediaan menjadi 11.602 pasang

Cellular models and assays to study NLRP3 inflammasome biology

The NLRP3 inflammasome is a multi-protein complex that initiates innate immunity responses when exposed to a wide range of stimuli, including pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs). Inflammasome activation leads to the release of the pro-inflammatory cytokines interleukin (IL)-1β and IL-18 and to pyroptotic cell death. Over-activation of NLRP3 inflammasome has been associated with several chronic inflammatory diseases. A deep knowledge of NLRP3 inflammasome biology is required to better exploit its potential as therapeutic target and for the development of new selective drugs. To this purpose, in the past few years, several tools have been developed for the biological characterization of the multimeric inflammasome complex, the identification of the upstream signaling cascade leading to inflammasome activation, and the downstream effects triggered by NLRP3 activation. In this review, we will report cellular models and cellular, biochemical, and biophysical assays that are currently available for studying inflammasome biology. A special focus will be on those models/assays that have been used to identify NLRP3 inhibitors and their mechanism of action

Simplified three-dimensional tissue clearing and incorporation of colorimetric phenotyping.

Tissue clearing methods promise to provide exquisite three-dimensional imaging information; however, there is a need for simplified methods for lower resource settings and for non-fluorescence based phenotyping to enable light microscopic imaging modalities. Here we describe the simplified CLARITY method (SCM) for tissue clearing that preserves epitopes of interest. We imaged the resulting tissues using light sheet microscopy to generate rapid 3D reconstructions of entire tissues and organs. In addition, to enable clearing and 3D tissue imaging with light microscopy methods, we developed a colorimetric, non-fluorescent method for specifically labeling cleared tissues based on horseradish peroxidase conversion of diaminobenzidine to a colored insoluble product. The methods we describe here are portable and can be accomplished at low cost, and can allow light microscopic imaging of cleared tissues, thus enabling tissue clearing and imaging in a wide variety of settings