Miracle-dz/UniFAR-FTUs huggingface dataset:
Planning Computational Biology Projects Using Agile Approach

Recent advancement in the biological sciences field led to an increase in the development of large biological software research projects. These projects are complex and interconnected and have proven to be hard to manage. In many cases, these projects are not completed within their deadlines and fail to provide the users with a reliable piece of software that can be managed and maintained in the future. This observation was also confirmed by scientists working in other research and scientific fields. It is well known that the non-deterministic nature of science requires it to be always evolving and changing. To meet such requirements using conventional software engineering practices will be a very hard goal to achieve. For this reason, I suggest the use of agile approaches such as Scrum, Kanban, and extreme programming, as an attractive choice to many developers working in many academic and scientific fields especially in areas such as computational biology. In this paper, I will discuss some biological software systems that used agile approaches in developing or enhancing their projects and I will look into the benefits gained from adopting those approaches and how it can benefit the outcome of many scientific projects.
Guest Editorial Introduction to the Focused Section on Medical Mechatronics

The six papers in this focused section were originally presented at the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob'06), held February 20-22, 2006, in Pisa, Italy. The first three papers illustrate mechatronic devices for rehabilitation applications; the fourth paper presents a mechatronic system for disabled people; and the last two papers deal with mechatronic devices and technologies for minimally invasive and teleoperated surgery. The papers are summarized here.
Organic Food Consumers Purchase Patterns – Insights from Croatian Market

Organic agriculture is a holistic production system, which sustains the natural soil activity, ecosystem and people. The new system is a reaction of producers of organic food to unsustainability of capital intensive agriculture. Organic food market develops progressively because of consumers’ increased interest in nutrition, health and environment protection, with the European market for organic food being the biggest market for organic food worldwide. Organic food market in Croatia is in the phase of rapid development with characteristics of mature markets. Taking into account the offer of organic food in Croatian big box retailers, the market is definitely between the growing and the developed market. Theoretical part of the paper will sum up findings about characteristics of organic food consumers and address their buying behaviour, motives for organic food purchase and perception about organic food compared to conventional food. Research results show existence of significant relationship between organic food purchase according to the region, education level, place of residence, financial status, personal monthly income and monthly household income. Further on, insights from organic food purchase patterns from Croatian market show that frequent organic food consumers consider organic food tastier and healthier than conventional, and consider that organic food with the eco-label is safer for consumption than the food without the eco-label. DOI: 10.5901/mjss.2013. v4n11p472
Supervised and unsupervised weight and delay adaptation learning in temporal coding spiking neural networks

Artificial neural networks are learning paradigms which mimic the biological neural system. The temporal coding Spiking Neural Network, a relatively new artificial neural network paradigm, is considered to be computationally more powerful than the conventional neural network. Research on the network of spiking neurons is an emerging field and has potential for wider investigation. This research explores alternative learning models with temporal coding spiking neural networks for clustering and classification tasks. Neurons are known to be operating in two modes namely, as integrators and coincidence detectors. Previous temporal coding spiking neural networks, realising spiking neurons as integrators, were utilised for analytical studies. Temporal coding spiking neural networks applied successfully for clustering and classification tasks realised spiking neurons as coincidence detectors and encoded input in formation in the connection delays through a weight adaptation technique. These learning models select suitably delayed connections by enhancing the weights of those connections while weakening the others. This research investigates the learning in temporal coding spiking neural networks with spiking neurons as integrators and coincidence detectors. Focus is given to both supervised and unsupervised learning through weight as well as through delay adaptation. Three novel models for learning in temporal coding spiking neural networks are presented in this research. The first spiking neural network model, Self- Organising Weight Adaptation Spiking Neural Network (SOWA_SNN) realises the spiking neuron as integrator. This model adapts and encodes input information in its connection weights. The second learning model, Self-Organising Delay Adaptation Spiking Neural Network (SODA_SNN) and the third model, Super vised Delay Adaptation Spiking Neural Network (SDA_SNN) realise the spiking neuron as coincidence detector. These two models adapt the connection delays in order to detect temporal patterns through coincidence detection. The first two models were developed for clustering applications and the third for classification tasks. All three models employ Hebbian-based learning rules to update the network connection parameters by utilising the difference between the input and output spike times. The proposed temporal coding spiking neural network models were implemented as discrete models in software and their characteristics and capabilities were analysed through simulations on three bench mark data sets and a high dimensional data set. All three models were able to cluster or classify the analysed data sets efficiently with a high degree of accuracy. The performance of the proposed models, was found to be better than the existing spiking neural network models as well as conventional neural networks. The proposed learning paradigms could be applied to a wide range of applications including manufacturing, business and biomedical domains.
Modeling of Bank Asset Management System based on Intelligent Agent

In this paper, we investigated the modeling of Bank Asset Management System(BAME) based on intelligent agent. To achieve this goal, we introduced several kinds of agents that show intelligent features. BAMS is a user friendly system and adopts fuzzy converting system and fuzzy matching system that returns reasonable similarity matching results. Generation function of the proximity degree is suggested. Fuzzification of investment type categories and feature values are defined, and generation of proximity degree is also derived. An example of bank asset management system is introduced and simulated. Investment type matching utilizing fuzzy measure is tested and it showed quite reasonable similarity matching results.
Comprehensive Model for Randomly Phase-Matched Frequency Conversion in Zinc-Blende Polycrystals and Experimental Results for 
ZnSe

With their natural randomness, polycrystalline materials as gain elements have opened an avenue for the development of ultrafast laser sources. The authors' model, based on the rigorous orientation of crystalline domains, lays the foundation for ultrafast three-wave interactions in a material, in terms of randomized polarizations and intensities. This work clarifies the potential of random phase matching in ultrafast applications, as well as the standard for nonlinear gain in this process, by comparison to the well-developed technology of quasi-phase matching.
Membrane Cholesterol Is a Biomechanical Regulator of Neutrophil Adhesion

Objective—The purpose of this study was to evaluate the role of membrane cholesterol on human neutrophil and HL-60 biomechanics, capture, rolling, and arrest to P-selectin– or IL-1–activated endothelium. Methods and Results—Methyl-β-cyclodextrin (MβCD) removed up to 73% and 45% of membrane cholesterol from HL-60 cells and neutrophils, whereas MβCD/cholesterol complexes resulted in maximum enrichment of 65% and 40%, respectively, above control levels. Cells were perfused at a venous wall shear rate of 100 s−1 over adherent P-selectin–coated 1-&mgr;m diameter beads, uncoated 10-&mgr;m diameter beads, P-selectin–coated surfaces, or activated endothelium. Elevated cholesterol enhanced capture efficiency to 1-&mgr;m beads and increased membrane tether growth rate by 1.5- to 2-fold, whereas cholesterol depletion greatly reduced tether formation. Elevated cholesterol levels increased tether lifetime by 17% in neutrophils and adhesion lifetime by 63% in HL-60 cells. Deformation of cholesterol-enriched neutrophils increased the contact time with 10-&mgr;m beads by 32% and the contact area by 7-fold. On both P-selectin surfaces and endothelial-cell monolayers, cholesterol-enriched neutrophils rolled more slowly, more stably, and were more likely to firmly arrest. Cholesterol depletion resulted in opposite effects. Conclusions—Increasing membrane cholesterol enhanced membrane tether formation and whole cell deformability, contributing to slower, more stable rolling on P-selectin and increased firm arrest on activated endothelium.
Circulating Anti-Immunoglobulin Antibodies in Recent-Onset Type I Diabetic Patients

Human sera from 51 recent-onset insulin-dependent (type I) diabetic patients and 47 unrelated control subjects were screened for the possible presence of circulating factors reacting with several anti-pancreatic islet monoclonal antibodies (MoAb.ISL) in solid-phase radioimmunoassay methods (the original goal being the detection of anti-idiotypic islet cell antibodies and/or specific islet cell antigen–bearing immune complexes). MoAbs from the parental myeloma cell line and purified immunoglobulins (Igs) from different animal species were controls. Type I diabetic sera showed significantly increased binding to MoAb.ISL-coated wells compared with normal subjects (P < .001). However, the same sera also tended to show a higher binding to the control (non–islet-related) MoAb. Sera from type I diabetic patients also reacted with horse, bovine, pig, rabbit, and goat IgG. Displacement of the binding has been obtained by F(ab′)2 and/or Fc fragments of IgG. Evidence has been obtained regarding a similar reaction with human IgM. All the sera were negative when tested for rheumatoid factor by nephelometry. The circulating antibodies described have been proven to be different from islet cell autoantibodies. An anti-Ig antibody is thus present in the sera of recent-onset diabetic patients and represents an additional immunological phenomenon with possible physiopathological and clinical significance.
Differential distribution of NAA and NAAG in human brain as determined by quantitative localized proton MRS

Quantitative proton magnetic resonance spectroscopy was performed in frontal, parietal and occipital white and gray matter of young adults with use of a fully relaxed, short‐echo time stimulated echo acquisition mode localization sequence at 2.0 T. Separate concentrations of the neuronal compounds N‐acetylaspartate (NAA) and N‐acetylaspartylglutamate (NAAG) were obtained by user‐independent spectral analysis (LCModel). Except for occipital gray matter in which an NAA concentration of 10.1±1.0 mM correlated with enhanced neuronal density in visual cortex, NAA was found to be homogeneously distributed throughout cortical white and gray matter at a concentration of 8.0–8.9 mM. NAAG concentrations of 1.5–2.7 mM were higher in white matter than levels of 0.6–1.5 mM found in gray matter, contributing up to 25% of total N‐acetyl‐containing compounds. The frontal to parieto‐occipital increase of both gray and white matter NAAG levels is also reflected in the distribution of total NAA. © 1997 John Wiley & Sons, Ltd.
Assessment of fetoplacental function by biochemical determinations

For 50 years the emphasis of obstetric management has shifted from the mother to the unborn child. Maternal mortality has fallen from rates of 4 per 1000 or greater to rates of 0-2 per 1000, so that the chances of a woman dying during pregnancy are hardly more than those if she were not pregnant over the same time period (Registrar General, 1972). But perinatal mortality at around 25 per 1000 continues to be well above the possible minimum; furthermore there will be two or three children severely damaged for every one which dies (Chard, 1974a). The prevention of perinatal mortality and morbidity might, in part, be achieved by intensification of the existing clinical approach. Yet the scope of purely clinical methods has probably reached its peak, and most advances are certain to involve laboratory-orientated technology, including electronic and biochemical methods for the assessment of fetal wellbeing and growth. With the exception of congenital abnormality, the placenta is the common denominator in many of the conditions which threaten fetal wellbeing. For the whole period of intrauterine life, the placenta has to act as lung, gut, kidney, and as a barrier to infection. Most ofthe biochemical methods are directed towards the study of this organ and its relationship with the fetus.
The NLRP1 Inflammasome Attenuates Colitis and Colitis-Associated Tumorigenesis

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins are a diverse family of pattern recognition receptors that are essential mediators of inflammation and host defense in the gastrointestinal system. Recent studies have identified a subgroup of inflammasome forming NLRs that modulate the mucosal immune response during inflammatory bowel disease (IBD) and colitis associated tumorigenesis. To better elucidate the contribution of NLR family members in IBD and cancer, we conducted a retrospective analysis of gene expression metadata from human patients. These data revealed that NLRP1, an inflammasome forming NLR, was significantly dysregulated in IBD and colon cancer. To better characterize the function of NLRP1 in disease pathogenesis, we used Nlrp1b−/− mice in colitis and colitis-associated cancer models. In this paper, we report that NLRP1 attenuates gastrointestinal inflammation and tumorigenesis. Nlrp1b−/− mice demonstrated significant increases in morbidity, inflammation, and tumorigenesis compared with wild-type animals. Similar to data previously reported for related inflammsome forming NLRs, the increased inflammation and tumor burden was correlated with attenuated levels of IL-1β and IL-18. Further mechanistic studies using bone marrow reconstitution experiments revealed that the increased disease pathogenesis in the Nlrp1b−/− mice was associated with nonhematopoietic-derived cells and suggests that NLRP1 functions in the colon epithelial cell compartment to attenuate tumorigenesis. Taken together, these data identify NLRP1 as an essential mediator of the host immune response during IBD and cancer. These findings are consistent with a model whereby multiple NLR inflammasomes attenuate disease pathobiology through modulating IL-1β and IL-18 levels in the colon.
A phase 2 study of the insulin‐like growth factor‐1 receptor inhibitor MK‐0646 in patients with metastatic, well‐differentiated neuroendocrine tumors

Neuroendocrine tumor (NET) cell lines frequently express both insulin‐like growth factor (IGF) ligand and the cognate IGF‐1 receptor (IGF‐1R) and, as such, potentially depend on the activation of IGF‐1R and its downstream effectors for growth and survival. Preclinical studies suggest that somatostatin analogs and mammalian target of rapamycin (mTOR) inhibitors exhibit antitumor activity against NETs through inhibition of IGF‐1‐dependent signaling, suggesting that IGF‐1R inhibition may be a promising therapeutic approach to NETs. Therefore, the authors of this report evaluated the safety and efficacy of MK‐0646, a fully human monoclonal antibody (MoAb) that binds to the IGF‐1R, as monotherapy in patients with metastatic, well‐differentiated NETs.
New Genus of Blood Fluke (Digenea: Schistosomatoidea) from Malaysian Freshwater Turtles (Geoemydidae) and its Phylogenetic Position Within Schistosomatoidea

Abstract Baracktrema obamai n. gen., n. sp. infects the lung of geoemydid turtles (black marsh turtle, Siebenrockiella crassicollis [type host] and southeast Asian box turtle, Cuora amboinensis) in the Malaysian states of Perak, Perlis, and Selangor. Baracktrema and Unicaecum Stunkard, 1925 are the only accepted turtle blood fluke genera having the combination of a single cecum, single testis, oviducal seminal receptacle, and uterine pouch. Baracktrema differs from Unicaecum by having a thread-like body approximately 30−50× longer than wide and post-cecal terminal genitalia. Unicaecum has a body approximately 8−12× longer than wide and terminal genitalia that are anterior to the distal end of the cecum. The new genus further differs from all other accepted turtle blood fluke genera by having a cecum that is highly convoluted for its entire length, a spindle-shaped ovary between the cirrus sac and testis, a uterine pouch that loops around the primary vitelline collecting duct, a Laurer's canal, and a dorsal common genital pore. Phylogenetic analysis of the D1–D3 domains of the nuclear large subunit ribosomal DNA (28S) revealed, with high nodal support and as predicted by morphology, that Baracktrema and Unicaecum share a recent common ancestor and form a clade sister to the freshwater turtle blood flukes of Spirorchis, paraphyletic Spirhapalum, and Vasotrema and that, collectively, these flukes were sister to all other tetrapod blood flukes (Hapalorhynchus + Griphobilharzia plus the marine turtle blood flukes and schistosomes). Pending a forthcoming emended morphological diagnosis of the family, the clade including Spirorchis spp. , paraphyletic Spirhapalum, Vasotrema, Baracktrema, and Unicaecum is a likely placeholder for “Spirorchiidae Stunkard, 1921” (type genus Spirorchis MacCallum, 1918; type species Spirorchis innominatus Ward, 1921). The present study comprises the 17th blood fluke known to infect geoemydid turtles and the first proposal of a new genus of turtle blood fluke in 21 yr.
Definition und Steuergrößen von (Hoch-)intensivem Intervalltraining in Bewegungstherapie & Gesundheitssport

Zusammenfassung Aufgrund ähnlicher und teilweise sogar höherer zentraler und periphererer Trainingsanpassungen im Vergleich zu niedrig-intensivem aerobem Ausdauertraining ist der Einsatz von Hochintensivem Intervalltraining (HIIT) seit einigen Jahren zum Standard in der Rehabilitation einiger Krankheitsbilder geworden. Welche Parameter zur Intensitätssteuerung während HIIT eingesetzt werden (können), hängt stark vom jeweiligen Krankheitsbild des Patienten ab. Klassische einfache physiologische Parameter sind die Herzfrequenz und die Herzfrequenzreserve. Hiermit wird das Training zumeist als % der maximalen Herzfrequenz bzw. Herzfrequenzreserve gesteuert. Kostengünstig einzusetzen sind Skalen des subjektiven Belastungsempfindens. Sollten diese einfachen Parameter nicht nutzbar sein, besteht die Möglichkeit, die maximale Leistung / Geschwindigkeit aus einem Stufentest als Orientierungsgröße zu nutzen.
Observations of variations in ERS-1 SAR image intensity associated with forest fires in Alaska

Investigations have shown that fires in boreal forests result in characteristic responses which are recorded on ERS-1 SAR imagery. Using one of the many fire signatures observed on ERS-1 SAR imagery, the analysis of the data revealed there is >10 dB in variation in image intensity within the burned areas on the SAR images. Possible explanations for this variation include increases in soil moisture, increased surface roughness exposed to the incoming microwave radiation, and damage to the vegetation canopy by the fire. >
Geometric Optimization of Planar Resonator for Wireless Strain Sensing Applications

With their simple geometries and capabilities for system integration, planar resonators have attracted considerable interest for microelectronics and microwave circuit applications. Together with MEMS technology and smart materials, they have been used on telecommunications, radio frequency identification, remote sensing, etc. The design of these devices is complicated by many conflicting requirements that must be taken into account. Often, researchers are compelled to carry out complex numerical computations and trial-and-error experiments to achieve acceptable performances. This paper reports on a multi-objective optimization method employed in the design of a planar resonator used as a passive wireless strain sensor. The technique can provide designers with a systematic and efficient approach to achieve the optimization of the geometry of the device based on the application requirements. Numerical results from nonlinear programming are shown and tradeoffs are discussed.
A novel gate driver with output having positive input voltage and negative double input voltage

This paper presents a gate driver, whose output has the positive input voltage and the negative double output voltage under only one positive-voltage source required. Such a gate driver can reduce the transient period of the gate driver and hence can reduce the corresponding switching loss. In addition, since the negative double output voltage is imposed on the input of the power switch during the turn-off period, the leakage current can be reduced, and hence the undesired energy loss can be decreased. The detailed operating principles are illustrated and some simulated and experimental results are provided to verify the effectiveness of the proposed scheme.
Data flushing data transfer protocol for IEEE 802.11 ad hoc wireless network

We present a data flushing data transfer (DFDT) protocol for IEEE 802.11 wireless ad hoc network. The basic mechanism of DFDT is quite the same as the distributed coordination function (DCF) of the medium access control (MAC) of IEEE 802.11, which uses a random access delay backoff time after a busy medium condition and RTS/CTS dialogue before sending actual payload data (direct data/ACK could also be used). The enhancement introduced by DFDT is mainly produced by the compilation process (CP), which fits as many MAC layer packets as possible into one physical layer packet within the limit of a predetermined length. By using the CP, we lower the protocol overhead, the packet arrival rate of the physical layer, and network contention all with one action. DFDT takes the advantages of the RTS/CTS mechanism but has less the overhead. Simulation results backed by numerical analysis show growing improvement in performance, limited by the saturation of the network, as the network load gets higher.