Miracle-dz/UniFAR-FTUs huggingface dataset:
Separable concatenated convolutional codes: The structure and properties of a class of codes for iterative decoding

In this paper a brief overview of the concept of iterative processing is provided. Then a code construction for convolutional codes, that results in a signal structure amenable to iterative processing, is studied. This construction is analogous to product coding for block codes. It is shown that the construction shares a number of properties with the product coding construction, including the property that it is commutative. The relationship between the free distance and the interleaving factors is examined, and then exemplified with computer simulation results.
Optimization of Microwave-Assisted Extraction (MAE) for the Isolation of Antioxidants from Basil (Ocimum basilicum L.) by Response Surface Methodology (RSM)

Abstract The recovery of antioxidants from basil (Ocimum basilicum L.) was modeled with the aid of response surface methodology (RSM) using microwave-assisted extraction (MAE). Face-centered central design (FCCD) was employed to optimize the MAE operational parameters including the extraction time (1 to 7 min), extraction temperature (30 to 120 °C), solid-to-solvent ratio (0.1 to 0.4), and solvent concentration (20 to 80% ethanol, v/v), and to obtain the best possible combinations of these parameters for a high antioxidant yield from basil. The total antioxidant capacity (TAC) was expressed in trolox (TR) equivalents per gram of dried sample (DS). Three of the operational parameters (temperature, extraction time and solvent concentration) were shown to have significant effect on the extraction efficiency of antioxidants in basil extracts (p < 0.05). The solvent concentration was shown to be the most significant factor on antioxidant yield obtained by MAE. There was a close relationship between experimental and predicted values using the proposed method. This optimized MAE method shows an application potential for the efficient extraction of antioxidants from basil in the food and pharmaceutical industries.
Development of sub-50-fs laser oscillator with mega-watt peak power for nonlinear applications

B Acknowledgement . D List of symbols and abbreviations . I List of tables . L List of Figures . M 1 Chapter 1: Introduction . 1 1.1 Intense short pulse infrared laser: Review and applications . 1 1.2 Limitations of the current work-horse Ti:sapphire laser. 4 1.3 The new era of Yb-doped lasers. 5 1.4 Background and Literature Review. 8 1.5 Advantage of bulk laser geometry . 9 1.6 Motivation . 11 1.7 Novelty and thesis contributions . 12 1.8 Organization of the thesis and related publications . 13 1.9 References . 16 2 Chapter 2: Continuous Wave Laser Design and Thermal Effects . 19 2.
Interleukin-15 Dendritic Cells Harness NK Cell Cytotoxic Effector Function in a Contact- and IL-15-Dependent Manner

The contribution of natural killer (NK) cells to the treatment efficacy of dendritic cell (DC)-based cancer vaccines is being increasingly recognized. Much current efforts to optimize this form of immunotherapy are therefore geared towards harnessing the NK cell-stimulatory ability of DCs. In this study, we investigated whether generation of human monocyte-derived DCs with interleukin (IL)-15 followed by activation with a Toll-like receptor stimulus endows these DCs, commonly referred to as “IL-15 DCs”, with the capacity to stimulate NK cells. In a head-to-head comparison with “IL-4 DCs” used routinely for clinical studies, IL-15 DCs were found to induce a more activated, cytotoxic effector phenotype in NK cells, in particular in the CD56bright NK cell subset. With the exception of GM-CSF, no significant enhancement of cytokine/chemokine secretion was observed following co-culture of NK cells with IL-15 DCs. IL-15 DCs, but not IL-4 DCs, promoted NK cell tumoricidal activity towards both NK-sensitive and NK-resistant targets. This effect was found to require cell-to-cell contact and to be mediated by DC surface-bound IL-15. This study shows that DCs can express a membrane-bound form of IL-15 through which they enhance NK cell cytotoxic function. The observed lack of membrane-bound IL-15 on “gold-standard” IL-4 DCs and their consequent inability to effectively promote NK cell cytotoxicity may have important implications for the future design of DC-based cancer vaccine studies.
Genetic Susceptibility to Multiple Sclerosis: The Role of FOXP3 Gene Polymorphism.

INTRODUCTION It is well recognized that both genetic and environmental factors play an important role in the pathogenesis of multiple sclerosis (MS). Immune pathogenesis of MS focuses on pathogenic CD4+ T lymphocytes. CD4+CD25+ regulatory T cells have suppressive function in this cell group. FOXP3 (forkhead boxP3) transcription factor is a key structure in the development and function of regulatory cells. Functional alterations in FOXP3 gene expression have been observed in various autoimmune diseases. METHODS We screened a non-synonymous coding single nucleotide polymorphism (exon +2710 C/T) (rs2232369) of human FOXP3 gene in 148 MS patients (118 with Relapsing Remitting MS, 30 with Secondary Progressive MS) and 102 age- and sex-matched healthy controls. The association of polymorphisms with susceptibility, and course of the disease was evaluated. RESULTS We could not detect any single nucleotide polymorphism in MS patients, however, polymorphic allele was detected in 3% of the control group. Consequently, a genetic association between the FOXP3 gene polymorphism and MS was not revealed. CONCLUSION The distribution of this polymorphism has not been screened in any other MS populations before. Although we could not succeed to find any association between susceptibility to MS and screened FOXP3 gene polymorphisms, we suggest that this particular polymorphism is not appropriate for these kind of studies in the future.
Appraisal of microbial inoculant of growth, yield and quality attributes of forage sorghum

The field experiments were conducted during kharif season of 2016 and 2017 at Punj ab Agricultural University, Regional Research Station, Bathinda, Punjab and Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana. The experiment was conducted in RCBD and replicated thrice. Biofertilizers, viz. Azotobacter sp. , Sphingobacterium sp. , Burkholderia sp. and Streptomyces Vadius were used for seed treatment of sorghum before sowing. Total nind treatments were evaluated, Tt : RDF, T2: RDF +Azotobacter sp. , T3: RDF+Azotobacter sp. +Sphingobacterium sp. , T4: RDF+Azotobacter sp. +Burkholderia sp, T5: RDF + Azotobacter sp. + Streptomyces badius , T6:75% of RDF + Azotobacter sp. , T7:75% of RDF +Azotobacter sp. + Sphingobacterium sp. , Ts : 75% of RDF + Azotobacter sp. + Burkholderia sp. , T9:75% of RDF + Azotobacter sp. + Streptomyces badius. The result revealed that nonetheless, in all the treatments in which microbial inoculants were applied along with chemical fertilizer, numeric increases were observed. The highest growth and yield attributes were observed in T4 treatment (RDF + Azotobacter sp.+Burkholderia sp.) at both the locations. The percentage increase in plant height, leaves per plant, tillers per plant, leaf/root ratio, green fodder yield and dry fodder yield in T4 treatment over control was 3.89,11.28,9.6,11.2,4.11,4.28 and4.72,12.44. 8.22,20.71,6.4,7.37, respectively at Bathinda and Ludhiana. This might be because ofmatching beneficial bacteria with their preferred crops, leading to optimized root colonization. Further, HCN content in all the treatments with microbial inoculants were slightly more than control but it was below permissible limit. In light of the results, it is concluded that the application of RDF + Azotobacter sp. + Burkholderia sp. recorded maximum green forage yield with good quality of forage sorghum.
Characterization and analysis of NTP amplification based DDoS attacks

Network Time Protocol based DDoS attacks saw a lot of popularity throughout 2014. This paper shows the characterization and analysis of two large datasets containing packets from NTP based DDoS attacks captured in South Africa. Using a series of Python based tools, the dataset is analysed according to specific parts of the packet headers. These include the source IP address and Time-to-live (TTL) values. The analysis found the top source addresses and looked at the TTL values observed for each address. These TTL values can be used to calculate the probable operating system or DDoS attack tool used by an attacker. We found that each TTL value seen for an address can indicate the number of hosts attacking the address or indicate minor routing changes. The Time-to-Live values, as a whole, are then analysed to find the total number used throughout each attack. The most frequent TTL values are then found and show that the migratory of them indicate the attackers are using an initial TTL of 255. This value can indicate the use of a certain DDoS tool that creates packets with that exact initial TTL. The TTL values are then put into groups that can show the number of IP addresses a group of hosts are targeting.
Hybrid Salient Object Extraction Approach with Automatic Estimation of Visual Attention Scale

In this work we present an intelligent approach to detection and extraction of salient objects. The described system is inspired by early processing stages of human visual system and is based on our previous work on the field of visual saliency. Building on our preceding system, which worked with a fixed visual attention scale, we develop a machine learning approach using an artificial neural network and genetic algorithm, estimating automatically the visual attention scale for each input image individually. The whole approach has low complexity and can be run in speed close to real-time on contemporary processors. Quantitative evaluation results of the described approach with visual attention scale estimation are compared to results obtained with a fixed scale and to results of two other existing salient object detection techniques. The system is a part of our work on an intelligent machine vision system, using visual saliency for unsupervised learning of objects.
Combining high-level causal reasoning with low-level geometric reasoning and motion planning for robotic manipulation

We present a formal framework that combines high-level representation and causality-based reasoning with low-level geometric reasoning and motion planning. The frame-work features bilateral interaction between task and motion planning, and embeds geometric reasoning in causal reasoning, thanks to several advantages inherited from its underlying components. In particular, our choice of using a causality-based high-level formalism for describing action domains allows us to represent ramifications and state/transition constraints, and embed in such formal domain descriptions externally defined functions implemented in some programming language (e.g., C++). Moreover, given such a domain description, the causal reasoner based on this formalism (i.e., the Causal Calculator) allows us to compute optimal solutions (e.g., shortest plans) for elaborate planning/prediction problems with temporal constraints. Utilizing these features of high-level representation and reasoning, we can combine causal reasoning, motion planning and geometric planning to find feasible kinematic solutions to task-level problems. In our framework, the causal reasoner guides the motion planner by finding an optimal task-plan; if there is no feasible kinematic solution for that task-plan then the motion planner guides the causal reasoner by modifying the planning problem with new temporal constraints. Furthermore, while computing a task-plan, the causal reasoner takes into account geometric models and kinematic relations by means of external predicates implemented for geometric reasoning (e.g., to check some collisions); in that sense the geometric reasoner guides the causal reasoner to find feasible kinematic solutions. We illustrate an application of this framework to robotic manipulation, with two pantograph robots on a complex assembly task that requires concurrent execution of actions. A short video of this application accompanies the paper.
Changes in immune parameters and their correction in human cases of tick‐borne encephalitis

Tick‐Borne Encephalitis virus (TBEV) causes dangerous central nervous system diseases in humans. General infection leads to the development of meningitis or encephalitis, which is characterized by swelling of the brain due to inflammation. Tetracyclines may act locally to moderate inflammation in the CNS. In this study, we investigated the potential clinical benefits of administering tetracycline hydrochloride to patients hospitalized due to suspected TBEV infection presenting with fever and evidence of a recent tick bite. We also characterized an acute immune response to TBEV by profiling certain cytokines and soluble receptors in Tetracycline‐treated and untreated patients. Increased serum levels of TNF‐α, IL‐1α and IL‐6 were found in all patients at admission.
Joint Design for MIMO Radar and Downlink Communication Systems Coexistence

This paper focuses on the problem of coexistence between a colocated multiple-in multiple-out (MIMO) radar and down-link communication systems. We propose an iterative algorithm to minimize the Cramer-Rao Bound (CRB) on the direction of arrival (DOA) of a target, accounting for the energy and similarity constraints. More Specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and then the communication weights are obtained by exploiting the block successive upper-bound minimization method (BSUM). Finally, numerical results are presented to evaluate the effectiveness of the proposed algorithm.
Modeling, design, and optimization of permanent magnet synchronous machines

Improvement of performance of robots has necessitated technological advances in control algorithms, mechanical structures, and electric machines. Running, legged robots have presented challenges in the area of electric machinery in particular. In addition to the low-speed, high-torque, low-mass requirements on the machines, the act of running results in an unconventional drive cycle that consists of brief periods of high torque followed by long stretches of minimal torque requirement, a performance envelope that is not matched by commercially-available machines. An optimized motor would dissipate the minimum possible power over the given drive cycle, lowering temperatures and potentially reducing required battery mass or extending range. These performance requirements have motivated faster modeling techniques to enable optimization of designs for these unconventional applications. This thesis presents a novel, fast modeling method for permanent magnet synchronous machines consisting of a hybrid model comprising an explicit Maxwell solution and a Flux Tube solution. The Maxwell solution is performed for the rotor and airgap of the machine, where geometries are simple and materials are homogeneous. The stator, with its geometric complexities and non-linear materials, is modeled with a lumped-parameter model based on flux tubes. The two models are then stitched together, forced to be self-consistent with boundary conditions, and allowed to converge. This captures effects such as cogging torque as well as saturation of the core materials. The method is approximately four orders of magnitude faster than a reference finite element program (0.01 s versus 100 s) for the same accuracy. The modeling method is implemented for two topologies of surface-mount permanent-magnet machines, an internal-rotor machine and an external-rotor machine. It is then used to optimize machine design to a given drive cycle, including effects of core loss. A machine is built to demonstrate the validity of the model and optimization method and test results match predictions of instantaneous torque to within 5% at the worst point. Cogging torque is another aspect of performance that is important to machines for robotics and other applications. These pulsations in torque caused by magnet alignment with geometric features in the stator result in undesired vibrations and
Cryptogauge symmetry and cryptoghosts for crypto-Hermitian Hamiltonians

We discuss the Hamiltonian H = p2/2 − (ix)2n+1 and the mixed Hamiltonian Hmixed = (p2 + x2)/2 − g(ix)2n+1. The Hamiltonians H and in some cases also Hmixed are crypto-Hermitian in a sense that, in spite of their apparent non-Hermiticity, a quantum spectral problem can be formulated such that the spectrum is real. We note that the corresponding classical Hamiltonian system can be treated as a gauge system, with the imaginary part of the Hamiltonian playing the role of the first class constraint. Several different nontrivial quantum problems can be formulated on the basis of this classical problem. We formulate and solve some such problems. We consider then the mixed Hamiltonian and find that its spectrum undergoes in certain cases a rather amazing transformation when the coupling g is sent to zero. There is an infinite set of exceptional points g(j)⋆ where a couple of eigenstates of H coalesce and their eigenvalues cease to be real. When quantization is done in the most natural way such that gauge constraints are imposed on quantum states, the spectrum should not be positive definite, but must involve the negative energy states (ghosts). We speculate that, in spite of the appearance of ghost states, unitarity might still be preserved.
The conserved metalloprotease invadolysin is present in invertebrate haemolymph and vertebrate blood

ABSTRACT We identified invadolysin, a novel essential metalloprotease, for functions in chromosome structure, cell proliferation and migration. Invadolysin also plays an important metabolic role in insulin signalling and is the only protease known to localise to lipid droplets, the main lipid storage organelle in the cell. In silico examination of the protein sequence of invadolysin predicts not only protease and lipase catalytic motifs, but also post-translational modifications and the secretion of invadolysin. Here we show that the protease motif of invadolysin is important for its role in lipid accumulation, but not in glycogen accumulation. The lipase motif does not appear to be functionally important for the accumulation of lipids or glycogen. Post-translational modifications likely contribute to modulating the level, localisation or activity of invadolysin. We identified a secreted form of invadolysin in the soluble fraction of invertebrate hemolymph (where we observe sexually dimorphic forms) and also vertebrate plasma, including in the extracellular vesicle fraction. Biochemical analysis for various post-translational modifications demonstrated that secreted invadolysin is both N- and O-glycosylated, but not apparently GPI-linked. The discovery of invadolysin in the extracellular milieu suggests a role for invadolysin in normal organismal physiology. Summary: In this study, we show that the conserved metalloprotease invadolysin is present in invertebrate hemolymph and vertebrate blood, suggesting the protein may function in organismal physiology.
An intragenic long noncoding RNA interacts epigenetically with the RUNX1 promoter and enhancer chromatin DNA in hematopoietic malignancies

RUNX1, a master regulator of hematopoiesis, is the most commonly perturbed target of chromosomal abnormalities in hematopoietic malignancies. The t(8;21) translocation is found in 30–40% of cases of acute myeloid leukemia (AML). Recent whole‐exome sequencing also reveals mutations and deletions of RUNX1 in some solid tumors. We describe a RUNX1‐intragenic long noncoding RNA RUNXOR that is transcribed as unspliced transcript from an upstream overlapping promoter. RUNXOR was upregulated in AML samples and in response to Ara‐C treatment in vitro. RUNXOR utilizes its 3′‐terminal fragment to directly interact with the RUNX1 promoter and enhancers and participates in the orchestration of an intrachromosomal loop. The 3′ region of RUNXOR also participates in long‐range interchromosomal interactions with chromatin regions that are involved in multiple RUNX1 translocations. These data suggest that RUNXOR noncoding RNA may function as a previously unidentified candidate component that is involved in chromosomal translocation in hematopoietic malignancies.
Effects of an Air Curtain on the Temperature Distribution in Refrigerated Vehicles Under a Hot Climate Condition

Refrigerated vehicle plays an essential role in the cold-chain applications. It directly affects the quality and shelf life of specialized perishable goods. However, the cold energy dissipation caused by natural convection through an open door during partial unloading breaks the isothermal cold environment and notably elevates the air temperature inside the refrigerated container. This temperature rise is harmful to the remaining food. In this study, an air curtain was introduced near the container doorway to attempt to reduce the cold energy dissipation caused by partial unloading. A numerical model was established to explore the effects of the key parameters of the air curtain such as the airflow rate, nozzle width, and jet angle on the air flow and temperature evolution inside the refrigerated container after the door is opened. The numerical results show that the key parameters need to be tailored to form a stable and effective air curtain for preventing the internal cold energy loss or external hot air invasion. An effective and stable air curtain was formed to make the inner air temperature increase only by about 3 °C from the initial temperature of 5 °C after the door was opened, when the jet velocity was set to 2 m/s, the nozzle width was set as 7.5 cm, and the jet angle was set between 0 deg and 15 deg. This work can offer significant guidance for the introduction of an effective air curtain in a refrigerated vehicle to avoid the failure of cold-chain transportation.
Sparse Logistic Regression for Text Categorization

This paper studies regularized logistic regression and its application to text categorization. In particular we examine a Bayesian approach, lasso logistic regression, that simultaneously selects variables and provides regularization. We present an efficient training algorithm for this approach, and show that the resulting classifiers are both compact and have state-of-the-art effectiveness on a range of text categorization tasks.
Windowed Attention Mechanisms for Speech Recognition

The usual attention mechanisms used for encoder-decoder models do not constrain the relationship between input and output sequences to be monotonic. To address this we explore windowed attention mechanisms which restrict attention to a block of source hidden states. Rule-based windowing restricts attention to a (typically large) fixed-length window. The performance of such methods is poor if the window size is small. In this paper, we propose a fully-trainable windowed attention and provide a detailed analysis on the factors which affect the performance of such an attention mechanism. Compared to the rule-based window methods, the learned window size is significantly smaller yet the model’s performance is competitive. On the TIMIT corpus this approach has resulted in a 17% (relative) performance improvement over the traditional attention model. Our model also yields comparable accuracies to the joint CTC-attention model on the Wall Street Journal corpus.
A Contraction Theory Approach to Stochastic Incremental Stability

We investigate the incremental stability properties of It ˆ s ochastic dynamical systems. Specifically, we derive a stochastic version of nonlinear contraction theory that p rovides a bound on the mean square distance between any two trajectories of a stochastically contracting syste m. This bound can be expressed as a function of the noise intensity and the contraction rate of the noise-free system . We illustrate these results in the contexts of nonlinear observers design and stochastic synchronization.