Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory-Augmented Neural Networks for Predictive Process Analytics

Process analytics involves a sophisticated layer of data analytics built over the traditional notion of process mining. The flexible execution of business process instances involves multiple critical decisions including what task to perform next and what resources to allocate to a task. In this paper, we explore the application of deep learning techniques for solving various process analytics related problems. Based on recent advances in the field we specifically look at memory-augmented neural networks (MANN)s and adapt the latest model to date, namely the Differential Neural Computer. We introduce two modifications to account for a variety of tasks in predictive process analytics: (i) separating the encoding phase and decoding phase, resulting dual controllers, one for each phase; (ii) implementing a write-protected policy for the memory during the decoding phase. We demonstrate the feasibility and usefulness of our approach by solving a number of common process analytics tasks such as next activity prediction, time to completion and suffix prediction. We also introduce the notion of MANN based process analytics recommendation machinery that once deployed can serve as an effective business process recommendation engine enabling organizations to answer various prescriptive process analytics related questions.Using real-world datasets, we benchmark our results against those obtained from the state-of-art methods. We show that MANNs based process analytics methods can acheive state-of-the-art performance and have a lot of value to offer for enterprise specific process anlaytics applications.
INTERACTION OF NANOSECOND LASER PULSES WITH BIOLOGICAL TISSUE PHANTOMS

The bubbles were generated by using a Q-switched Nd:YAG laser (Continuum YG 671-10) which delivers light pulses at a wavelength of 1064 nm with energies of up to 250 mJ and a pulse duration of 6 ns. The elastic-plastic media consist of a polyacrylamide (PAA) gels whose elastic properties can be controlled by modifying the water content of the sample. The PAA sample was mounted in a teflon holder and completely immersed in water during experiments. Achromats were used for beam collimation and focusing to minimize spherical aberrations, and for the same purpose an ophthalmic contact lens corrected for an air water transition (Rodenstock RYM) was built into the cuvette wall [7]. The dynamics of the cavitation bubble was recorded with a high-speed image converter camera (Hadland Photonics, Imacon 792) using a slow scan CCD camera system (Photometrics AT200A) with a 1317 x 1035 pixel array. During each laser exposure, the pulse energy was measured using a pyroelectric energy meter (Laser Precision Rj 7100). The pulse-to-pulse fluctuations of the laser energy were in the range of ±3%. The pressure of the shock wave emitted during optical breakdown and first bubble collapse was measured using a PVDF hydrophone (Ceram) with a rise time of 12 ns, an active area of 1 mm 2 , and a sensitivity of 21 mV/MPa. The elastic-plastic media consisted of transparent gels of polyacryalmide (PAA) with a water content of 95%, 85%, 80%, and 70%, respectively. For 70% water content, 60 grams acrylamid and 1.6 grams bis
Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.
Critical review on friction stir welding of aluminium to copper

The status quo of aluminium-to-copper joining by friction stir welding (FSW) drastically changed in recent years, as a result of the increased interest of the scientific community on this subject. Actually, since 2006 a large increase in the number of research groups addressing Al–Cu FSW has been witnessed all over the world, together with a significant increase in the amount of published studies. A chronological perspective on the evolution in Al–Cu FSW research is provided in this work, highlighting the pioneer and original contribution of several researchers to the current knowledge on the subject. Detailed and comprehensive investigations on the material flow mechanisms, the phenomena governing the formation and distribution of intermetallic phases during Al–Cu FSW, their relations with the welding parameters and their impact on the morphological, structural and mechanical properties of the welds are thoroughly discussed. The main findings reported in the literature are summarised in thematic tables.
The trifunctional antibody catumaxomab for the treatment of malignant ascites due to epithelial cancer: Results of a prospective randomized phase II/III trial

Malignant ascites is a common manifestation of advanced cancers, and treatment options are limited. The trifunctional antibody catumaxomab (anti‐epithelial cell‐adhesion molecule x anti‐CD3) represents a targeted immunotherapy for the intraperitoneal (i.p.) treatment of malignant ascites secondary to epithelial cancers. In this phase II/III trial (EudraCT 2004‐000723‐15; NCT00836654), cancer patients (n = 258) with recurrent symptomatic malignant ascites resistant to conventional chemotherapy were randomized to paracentesis plus catumaxomab (catumaxomab) or paracentesis alone (control) and stratified by cancer type (129 ovarian and 129 nonovarian). Catumaxomab was administered as an i.p. infusion on Days 0, 3, 7 and 10 at doses of 10, 20, 50 and 150 μg, respectively. The primary efficacy endpoint was puncture‐free survival. Secondary efficacy parameters included time to next paracentesis, ascites signs and symptoms and overall survival (OS). Puncture‐free survival was significantly longer in the catumaxomab group (median 46 days) than the control group (median 11 days) (hazard ratio = 0.254: p < 0.0001) as was median time to next paracentesis (77 versus 13 days; p < 0.0001). In addition, catumaxomab patients had fewer signs and symptoms of ascites than control patients. OS showed a positive trend for the catumaxomab group and, in a prospectively planned analysis, was significantly prolonged in patients with gastric cancer (n = 66; 71 versus 44 days; p = 0.0313). Although adverse events associated with catumaxomab were frequent, they were manageable, generally reversible and mainly related to its immunologic mode of action. Catumaxomab showed a clear clinical benefit in patients with malignant ascites secondary to epithelial cancers, especially gastric cancer, with an acceptable safety profile.
Genome-Wide Analysis Characterization and Evolution of SBP Genes in Fragaria vesca, Pyrus bretschneideri, Prunus persica and Prunus mume

The SQUAMOSA promoter binding protein (SBP)-box proteins are plant-specific transcriptional factors in plants. SBP TFs are known to play important functions in a diverse development process and also related in the process of evolutionary novelties. SBP gene family has been characterized in several plant species, but little is known about molecular evolution, functional divergence and comprehensive study of SBP gene family in Rosacea. We carried out genome-wide investigations and identified 14, 32, 17, and 17 SBP genes from four Rosacea species (Fragaria vesca, Pyrus bretschneideri, Prunus persica and Prunus mume, respectively). According to phylogenetic analysis arranged the SBP protein sequences in seven groups. Localization of SBP genes presented an uneven distribution on corresponding chromosomes of Rosacea species. Our analyses designated that the SBP genes duplication events (segmental and tandem) and divergence. In addition, due to highly conserved structure pattern of SBP genes, recommended that highly conserved region of microsyneteny in the Rosacea species. Type I and II functional divergence was detected among various amino acids in SBP proteins, while there was no positive selection according to substitutional model analysis using PMAL software. These results recommended that the purifying selection might be leading force during the evolution process and dominate conservation of SBP genes in Rosacea species according to environmental selection pressure analysis. Our results will provide basic understanding and foundation for future research insights on the evolution of the SBP genes in Rosacea.
The Arcuate Estrogen-Regulated Transcriptome: Estrogen Response Element–Dependent and –Independent Signaling of ER&agr; in Female Mice

To influence energy homeostasis and reproduction, 17β-estradiol (E2) controls the arcuate nucleus (ARC) through multiple receptor-mediated mechanisms, but primarily via estrogen receptor (ER) α, which signals through both estrogen response element (ERE)-dependent and -independent mechanisms. To determine ERα-mediated, ERE-dependent, and ERE-independent E2 signaling in the ARC, we examined the differential regulation of the mouse arcuate transcriptome by E2 using three mice genotypes: (1) wild-type, (2) ERα knock-in/knockout (ERE-independent mechanisms), and (3) total ERα knockout (ERα-independent mechanisms). Females were ovariectomized and injected with oil or E2, and RNA sequencing on the ARC was used to identify E2-regulated genes in each genotype. Our results show that E2 regulates numerous genes involved in cell signaling, cytoskeleton structure, inflammation, neurotransmission, neuropeptide production, and transcription. Furthermore, ERE-independent signaling regulates ARC genes expressed in kisspeptin neurons and transcription factors that control the hypothalamic/pituitary/gonadal axis. Interestingly, a few genes involved in mitochondrial oxidative respiration were regulated by E2 through ERα-independent signaling. A comparison within oil- and E2-treated females across the three genotypes suggests that genes involved in cell growth and proliferation, extracellular matrices, neuropeptides, receptors, and transcription are differentially expressed across the genotypes. Comparing with previously published chromatin immunoprecipitation sequencing analysis, we found that ERE-independent regulation in the ARC is mainly mediated by tethering of ERα, which is consistent with previous findings. We conclude that the mouse arcuate estrogen-regulated transcriptome is regulated by multiple receptor-mediated mechanisms to modulate the central control of energy homeostasis and reproduction, including novel E2-responsive pathways.
Novel 3D Hybrid Nanofiber Aerogels Coupled with BMP‐2 Peptides for Cranial Bone Regeneration

An ideal synthetic bone graft is a combination of the porous and nanofibrous structure presented by natural bone tissue as well as osteoinductive biochemical factors such as bone morphogenetic protein 2 (BMP‐2). In this work, ultralight 3D hybrid nanofiber aerogels composed of electrospun PLGA‐collagen‐gelatin and Sr–Cu codoped bioactive glass fibers with incorporation of heptaglutamate E7 domain specific BMP‐2 peptides have been developed and evaluated for their potential in cranial bone defect healing. The nanofiber aerogels are surgically implanted into 8 mm × 1 mm (diameter × thickness) critical‐sized defects created in rat calvariae. A sustained release of E7‐BMP‐2 peptide from the degradable hybrid aerogels significantly enhances bone healing and defect closure over 8 weeks in comparison to unfilled defects. Histomorphometry and X‐ray microcomputed tomography (µ‐CT) analysis reveal greater bone volume and bone formation area in case of the E7‐BMP‐2 peptide loaded hybrid nanofiber aerogels. Further, histopathology data divulged a near complete nanofiber aerogel degradation along with enhanced vascularization of the regenerated tissue. Together, this study for the first time demonstrates the fabrication of 3D hybrid nanofiber aerogels from 2D electrospun fibers and their loading with therapeutic osteoinductive BMP‐2 mimicking peptide for cranial bone tissue regeneration.
Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation

In the image processing pipeline of almost every digital camera, there is a part for removing the influence of illumination on the colors of the image scene. Tuning the parameter values of an illumination estimation method for maximal accuracy requires calibrated images with known ground-truth illumination, but creating them for a given sensor is time-consuming. In this paper, the green stability assumption is proposed that can be used to fine-tune the values of some common illumination estimation methods by using only non-calibrated images. The obtained accuracy is practically the same as when training on calibrated images, but the whole process is much faster since calibration is not required and thus time is saved. The results are presented and discussed. The source code website is provided in Section Experimental Results.
Microwave Properties in BaO-TiO2 System Added by ZrO2 and WO3

Both BaTi4O9 and Ba2Ti9O20 have the best microwave properties among many compounds in BaO-TiO2 system. The microwave performance of the ceramics in BaO-TiO2 system, which were prepared by conventional solid state method, was investigated in this paper. The study indicates that the (Ti,Zr)/Ba ratio has a great effect on the dielectric properties of the ceramic due to different BaTi4O9/Ba2Ti9O20 ratio. The pure BaTi4O9 ceramic exhibits the most outstanding microwave properties, with εr=35.55 and Q×f=43300GHz. On the contrary, the dielectric property of the pure Ba2Ti9O20 ceramic was not good enough, which should be doped with some additive additions. WO3 was incorporated into the system and the sintering temperature was adjusted to improve the microwave dielectric property. The Q×f was increased to 38000GHz by adding 1.35mol% WO3 due to the formation of a little BaWO4 phase. When sintered at a higher temperature (1380°C), the BaO-TiO2 system ceramic has εr =37.04 and Q×f =44874GHz.
Bioavailability of phosphorus in various phosphate sources using body weight and toe ash as response criteria.

The relative bioavailability values of P from seven sources were determined using male chickens fed a basal corn-soybean meal diet (.40% total P and 1.10% Ca) with varying levels of test and standard phosphates from 0 to 3 wk of age. Each of seven test phosphates was added to the basal diet at . 05, . 08, . 12, . 17, . 23, and . 32% levels. In addition, standard diets were formulated by adding the same levels of P plus . 44 and . 60% levels from dicalcium phosphate dihydrate (CaHPO4.2H2O) to the same basal diet. Each of the 42 test diets was fed to two pens of 10 chicks each, and each of the standard diets was fed to six pens of 10 chicks each. Three-week body weight gain and percentage ash of dried toe data were fitted with nonlinear (asymptotic and sigmoidal) regression equations, and the ratios of regression coefficients were used to determine the bioavailability of various test phosphates relative to the reference standard. Based on the asymptotic regression equation of body weight gain and on the sigmoidal regression equation of toe ash on the percentage of P added to the diets from the seven phosphate sources, the average relative bioavailability of the P (compared with the standard given a value of 100%) was as follows: Lucaphos-48, 88.4%; Lucaphos-40, 95.1%; Rukana, 83.7%; Cefkaphos-N, 104.8%; phosphoric acid, 93.0%; monocalcium phosphate monohydrate [Ca(H2PO4)2.H2O], 111.8%; and Biophos, 92.0%. A difference of 7.7% units for the average bioavailability of the P was required for significance (P < .05). (ABSTRACT TRUNCATED AT 250 WORDS)
A dystrophic Duchenne mouse model for testing human antisense oligonucleotides

Duchenne muscular dystrophy (DMD) is a severe muscle-wasting disease generally caused by reading frame disrupting mutations in the DMD gene resulting in loss of functional dystrophin protein. The reading frame can be restored by antisense oligonucleotide (AON)-mediated exon skipping, allowing production of internally deleted, but partially functional dystrophin proteins as found in the less severe Becker muscular dystrophy. Due to genetic variation between species, mouse models with mutations in the murine genes are of limited use to test and further optimize human specific AONs in vivo. To address this we have generated the del52hDMD/mdx mouse. This model carries both murine and human DMD genes. However, mouse dystrophin expression is abolished due to a stop mutation in exon 23, while the expression of human dystrophin is abolished due to a deletion of exon 52. The del52hDMD/mdx model, like mdx, shows signs of muscle dystrophy on a histological level and phenotypically mild functional impairment. Local administration of human specific vivo morpholinos induces exon skipping and dystrophin restoration in these mice. Depending on the number of mismatches, occasional skipping of the murine Dmd gene, albeit at low levels, could be observed. Unlike previous models, the del52hDMD/mdx model enables the in vivo analysis of human specific AONs targeting exon 51 or exon 53 on RNA and protein level and muscle quality and function. Therefore, it will be a valuable tool for optimizing human specific AONs and genome editing approaches for DMD.
Dissipative control for Markov jump non-linear stochastic systems based on T–S fuzzy model

The dissipative analysis and control problems for a class of Markov jump non-linear stochastic systems (MJNSSs) are investigated. A sufficient condition for the dissipativity of MJNSSs is given in terms of coupled non-linear Hamilton–Jacobi inequalities (HJIs). Generally, it is difficult to solve the coupled HJIs. In this paper, based on T–S fuzzy model, the dissipative analysis and controller design for MJNSSs is proposed via solving a set of linear matrix inequalities (LMIs) instead of HJIs. Finally, a numerical example is presented to show the effectiveness of the proposed method.
Nuclear export receptor CRM1 recognizes diverse conformations in nuclear export signals

Nuclear export receptor CRM1 binds highly variable nuclear export signals (NESs) in hundreds of different cargoes. Previously we have shown that CRM1 binds NESs in both polypeptide orientations (Fung et al., 2015). Here, we show crystal structures of CRM1 bound to eight additional NESs which reveal diverse conformations that range from loop-like to all-helix, which occupy different extents of the invariant NES-binding groove. Analysis of all NES structures show 5-6 distinct backbone conformations where the only conserved secondary structural element is one turn of helix that binds the central portion of the CRM1 groove. All NESs also participate in main chain hydrogen bonding with human CRM1 Lys568 side chain, which acts as a specificity filter that prevents binding of non-NES peptides. The large conformational range of NES backbones explains the lack of a fixed pattern for its 3-5 hydrophobic anchor residues, which in turn explains the large array of peptide sequences that can function as NESs. DOI: http://dx.doi. org/10.7554/eLife.23961. 001
Molecular docking based screening of Noggin inhibitors

Noggin (NOG) a BMP (bone morphogenetic protein) antagonist plays a key role in preferentially driving a subset of breast cancer cells towards the bone and causing osteolytic lesions leading to severe pain and discomfort in the patients. Owing to its role in bone metastasis, NOG could be promising molecular target in bone metastasis and that identifying small molecule inhibitors could aid in the treatment. Towards identifying cognate inhibitors of NOG, structure based virtual screen was employed. A total of 8.5 million ligands from e-molecule database were screened at a novel binding site on NOG identified by the Sitemap tool, employing GLIDE algorithm. Potential eight molecules were selected based on the Glide score, binding mode and H-bond interactions. Free energy of binding was calculated using Molecular mechanics based MMGBSA and the obtained energy was used in the prioritizing the compounds with the similar structures and glide score. Further, the compounds were evaluated for their druggability employing physico-chemical property analysis. Our study helped in identifying novel potential NOG inhibitors that can further be validated using in-vivo and in-vitro studies and these molecules can also be employed as tool compounds to study the functions of BMP.
Path Consistency Learning in Tsallis Entropy Regularized MDPs

We study the sparse entropy-regularized reinforcement learning (ERL) problem in which the entropy term is a special form of the Tsallis entropy. The optimal policy of this formulation is sparse, i.e.,~at each state, it has non-zero probability for only a small number of actions. This addresses the main drawback of the standard Shannon entropy-regularized RL (soft ERL) formulation, in which the optimal policy is softmax, and thus, may assign a non-negligible probability mass to non-optimal actions. This problem is aggravated as the number of actions is increased. In this paper, we follow the work of Nachum et al. (2017) in the soft ERL setting, and propose a class of novel path consistency learning (PCL) algorithms, called {\em sparse PCL}, for the sparse ERL problem that can work with both on-policy and off-policy data. We first derive a {\em sparse consistency} equation that specifies a relationship between the optimal value function and policy of the sparse ERL along any system trajectory. Crucially, a weak form of the converse is also true, and we quantify the sub-optimality of a policy which satisfies sparse consistency, and show that as we increase the number of actions, this sub-optimality is better than that of the soft ERL optimal policy. We then use this result to derive the sparse PCL algorithms. We empirically compare sparse PCL with its soft counterpart, and show its advantage, especially in problems with a large number of actions.