Miracle-dz/UniFAR-FTUs huggingface dataset:
A COMMUNICATION MODEL FOR VIRTUAL COLLABORATION

Globalization and the changing structures of organizations have created work groups that are distributed across space (different sites) and time. Collaboration among and between organizations is needed to support outsourcing strategies. As organizations focus on long term outsourcing and off-shoring relationships, effective communication is often seen as an important factor contributing to the success of individuals, project teams, and organizational growth. The adoption of global business models are enabled by the deployment of advanced technology to extend the usefulness of IT in support of distributed work environments. This research focuses on communication medium, decision quality, and group cohesiveness as important factors in determining the effectiveness of virtual teams.
On Rivalry, Variety and Spillovers in Endogenous Growth

Evidence shows that firms build their market position by consistently investing in R&D over time and accumulating knowledge protected by secrecy, patents and other appropriability devices. To explore the macroeconomic implications of this fact, I construct an economy where oligopolistic firms establish in- house R&D programs to produce a continuous flow of cost-reducing (incremental) innovations. Firms compete for sales and resources. In symmetric equilibrium, the number of firms determines concentration and firm size. These determine the scale and the efficiency of R&D operations and the (average) rate of innovation. If the number of firms is exogenous, one can study the relationship between the number of firms and the rate of growth of the economy. This exercise gives a first intuition about the forces at work. Static economies of scale due to product and knowledge variety yield increasing returns to the number of firms. A large number of firms leads to high output, high (aggregate) R&D, and fast growth. Offsetting this force, market fragmentation leads to small firms, small R&D programs, and slow growth. The number of firms, in addition, must be endogenous and determined jointly with the rate of growth by the zero-profit condition. Price, investment, entry, and exit decisions are now interdependent. In particular, R&D is a fixed (sunk) cost and is negatively related to the number of firms. This feed-back reinforces the market fragmentation effect and yields additional interactions. Many parameters no longer have the effects predicted by standard models. For example, the scale effect of population size is negative. The intuition is simple. Large markets have many firms, high output, and high aggregate R&D. Market fragmentation offsets this force and results in small firms and slow growth. These interactions generate a market allocation of resources that is not Pareto optimal. I discuss the nature of this distortion.
Intelligent Crossover and Mutation Technique to Control Bloat for Breast Cancer Diagnosis

Breast cancer affects several people at present time. Diagnosis which determines whether the cancer is benign or malignant requires a lot of effort from doctors and physician. Early diagnosis may save many lives. Accurate classification plays an important role in medical diagnosis. Genetic programming is a machine learning algorithm which now days excelling in classification field. But Genetic programming generally face the problem of code bloating in which an increase in average tree size is found without a corresponding increase in fitness. In this paper we are proposing a new technique for solving the problem of bloat and for increasing classification accuracy. The technique is known as intelligent crossover and mutation technique. This technique is a combination of hill climbing and conventional method which will be applied on both crossover and mutation operator. To demonstrate this, we had taken WBC dataset from UCI repository which has 2 classes and 9 features and we have compared classification accuracy of our method with standard crossover and FEDS crossover. Our classification accuracy was 97.5% for 50-50 training and testing methodology 95% for 60-40, 99% for 70-30, 99.5% for 80-20 and 99.6% for 10 fold cross validation technique. This shows our method can be used for medical diagnosis as it provides good results.
Improvement of Eosinophilic Otitis Media by Optimized Asthma Treatment

Eosinophilic otitis media (EOM) shows a very high rate of association with asthma, and intractable otitis media involves marked eosinophil infiltration into the middle ear. The middle ear space is connected to the nasopharynx by the Eustachian tube, and it is considered a part of the upper respiratory tract. Allergic rhinitis and asthma often coexist as chronic inflammatory diseases of the upper and lower airways, respectively, and have an impact on each other. In fact, inhaled corticosteroids reduce seasonal eosinophilia systemically in the circulation and locally in the nasal mucosa, as well as attenuate seasonal nasal symptoms. We report a case of EOM associated with adult-onset asthma that improved following optimal asthma therapy after changing the treatment from inhaled fluticasone propionate (FP) (200 µg b.i.d.) to a combination of FP/salmeterol (250/50 µg b.i.d.). This result supports the hypothesis that EOM and asthma are closely linked, presenting as different manifestations of a similar disease syndrome.
Evolution of brain ontogenetic growth under ecological challenges

Large brains are metabolically expensive but support skills (or cognitive abilities, knowledge, information, etc.) that allow overcoming ecological and social challenges, with social challenges being thought to strongly promote large-brain evolution by causing evolutionary arms races in cognition yielding exaggerated brain sizes. We formulate a mathematical model that yields quantitative predictions of brain and body mass throughout ontogeny when individuals evolve facing ecological but no social challenges. We find that ecological challenges alone can generate adult brain and body mass of ancient human scale, showing that evolutionary arms races in cognition are not necessary for extreme brain sizes. We show that large brains are favored by intermediately challenging ecological environments where skills are moderately effective and metabolically expensive for the brain to maintain. We further show that observed correlations of cognitive abilities and brain mass can result from saturation with skill maintenance of the brain metabolic rate allocated to skills.
Strongyloides stercoralis Infection in Alcoholic Patients

The course of Strongyloides stercoralis infection is usually asymptomatic with a low discharge of rhabditoid larva in feces. However, the deleterious effects of alcohol consumption seem to enhance the susceptibility to infection, as shown by a fivefold higher strongyloidiasis frequency in alcoholics than in nonalcoholics. Moreover, the association between S. stercoralis infection and alcoholism presents a risk for hyperinfection and severe strongyloidiasis. There are several possible mechanisms for the disruption of the host-parasite equilibrium in ethanol-addicted patients with chronic strongyloidiasis. One explanation is that chronic ethanol intake stimulates the hypothalamic-pituitary-adrenal (HPA) axis to produce excessive levels of endogenous cortisol, which in turn can lead to a deficiency in type 2 T helper cells (Th2) protective response, and also to mimic the parasite hormone ecdysone, which promotes the transformation of rhabditiform larvae to filariform larvae, leading to autoinfection. Therefore, when untreated, alcoholic patients are continuously infected by this autoinfection mechanism. Thus, the early diagnosis of strongyloidiasis and treatment can prevent serious forms of hyperinfection in ethanol abusers.
Using Genetic Algorithms for Inductive Learning

Inductive learning techniques can be utilised to build a set of IF-THEN rules from a given example data set. This paper presents a new technique for inductive learning called GAIL (Genetic Algorithm for Inductive Learning) which is based on Genetic Algorithms. Common algorithms for inductive learning are briefly reviewed. The GAIL algorithm is described and results are shown for two benchmark data sets. The results of GAIL are compared against standard inductive learning algorithms.
MIMO DOWNLINK PRECODING WITH CHANNEL MISMATCH ERROR FOR SIMPLIFIED RECEIVER

Recently research has been done on linear precoder design to minimize the receiver complexity. In our work, we design the linear precoder for the multiple input multiple output (MIMO) wireless communication system with multiple antennas at the base station (BS) and users each with multiple receiver antennas. Previous works on linear precoder design assume that perfect Channel State Info(CSI) is available at the Base station. But channel estimation error is unavoidable, due to the presence of noise in the channel estimation and due to feedback quantization. In a system employing Time Division Duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. Channel estimation errors occur due to the presence of background noise in the estimated signal. We derive an MMSE based precoding technique for a MIMO system that considers channel estimation errors as an integral part of the system design. The proposed precoding technique significantly improves the average bit error rate (BER).
Robust speech enhancement techniques for ASR in non-stationary noise and dynamic environments

In the current ASR systems the presence of competing speakers greatly degrades the recognition performance. This phenomenon is getting even more prominent in the case of hands-free, far-field ASR systems like the “Smart-TV” systems, where reverberation and non-stationary noise pose additional challenges. Furthermore, speakers are, most often, not standing still while speaking. To address these issues, we propose a cascaded system that includes Time Differences of Arrival estimation, multi-channel Wiener Filtering, nonnegative matrix factorization (NMF), multi-condition training, and robust feature extraction, whereas each of them additively improves the overall performance. The final cascaded system presents an average of 50% and 45% relative improvement in ASR word accuracy for the CHiME 2011(non-stationary noise) and CHiME 2012 (non-stationary noise plus speaker head movement) tasks, respectively.
Enhancement of epidermal regeneration by biosynthetic epidermal growth factor

Epidermal regeneration depends on mitosis and migration of keratinocytes. Epidermal growth factor is known to stimulate growth of keratinocytes in vitro, thus it might be expected to promote wound healing. The results of this study show that topical application of biosynthetic human epidermal growth factor accelerates epidermal regeneration in split-thickness wounds and partial-thickness burns. The significant enhancement of epidermal regeneration suggests the potential for clinical use of epidermal growth factor for accelerating healing of burns, wounds from trauma, diabetic ulcers, skin graft donor sites, and others.
Tracking the development of the petaloid fertile stamen in Canna indica: insights into the origin of androecial petaloidy in the Zingiberales

The order Zingiberales comprises ∼2500 species of tropical to subtropical plants, including agriculturally (e.g. banana, ginger) and horticulturally (e.g. cannas, heliconias, bird-of-paradise) important plants. Throughout the evolution of this order, the stamens have been modified from the ancestral filamentous structures that produce pollen (seen in Banana flowers) to petal-like structures that no longer bear pollen sacs (seen in Canna flowers). This results in a reduction of pollen, but an effective increase in the overall size of the floral display and perhaps in the efficacy of specialized pollinators by converting stamens into ‘petals’. This study investigates the genetic mechanisms that are involved in making petal-like structures in place of pollen-producing stamens.
A context-driven adaptation process for service-based applications

When building service-oriented systems the evolution of requirements and context is the norm rather than the exception. Therefore, it is important to make sure that the system is able to evolve as well without necessarily starting a completely new development process, and possibly on the fly. In this paper we specifically focus on the role of the context in the adaptation activities. For us context has various different facets as it includes information ranging from the situation in which users exploit a service-based application to the conditions under which the component services can be exploited. We elaborate on how and when the context should be defined, exploited, and evolved, and on the impact it has on the various activities related to adaptation of service-based applications. We use a case study to exemplify our first findings on this subject.
A Proof of the MV Matching Algorithm

The Micali-Vazirani (MV) algorithm for maximum cardinality matching in general graphs, which was published in 1980 \cite{MV}, remains to this day the most efficient known algorithm for the problem. This paper gives the first complete and correct proof of this algorithm. Central to our proof are some purely graph-theoretic facts, capturing properties of minimum length alternating paths; these may be of independent interest. An attempt is made to render the algorithm easier to comprehend.
Models of Financial System Fragility

This survey analyses two types of models: 1. Models based on assumptions of monetary and financial market equilibrium disturbance, in line with mainstream thinking according to which if there is a self-regulating market the units would have rational expectations, and the crisis would be a temporary phenomenon caused by exogenous shocks. Here are the main objectives and features characteristic of three generations of models; 2. Models based on financial instability hypothesis, taking into account the dynamics of financial market, as well as the role of uncertainty, interdependency and dynamic complexity. We present here Minsky’s concept of financial instability and then analyse the content of some simplified models.
Australia's Oceans Policy: Ten Years of Policy Implementation

The release of Australia’s Oceans Policy (AOP) in 1998 was recognised in Australia and internationally as a milestone in marine resource management. This policy set out for the first time a comprehensive, national approach to ecosystem based ocean management that covered Australia’s vast ocean domain. It also sought to integrate sectoral and jurisdictional interests through the establishment of new institutions and implementation methods. During the ten years of implementation the original aims of the policy have changed reflecting a lack of integration; Federal government ownership of the policy; institutional restructuring; and a lengthy implementation process. This paper analyses these changes and discusses what can be learned from the development and implementation of this ‘new’ policy.
Quantum-Inspired Immune Evolutionary Algorithm

The quantum-inspired evolutionary algorithm (QEA) is a probabilistic algorithm based on the quantum computing, which combines some principles such as concepts of qubits and superposition of states. QEAs can improve the traditional evolutionary algorithm effectively. However, they are easy to be trapped into the local deceptive peak, and the operations in QEA lack the capability of meeting an actual situation, so that some torpidity often appears when solving problems. In this paper, a new improved quantum-inspired immune evolutionary algorithm (QIEA) is proposed to overcome the shortcoming of the conventional QEAs. The new QIEA combines the main mechanisms of immune theory and every individual of each chromosome will make its own dynamic clone to build its new sub-swarm; then every new chromosome will be mutation in its low bit; at last, the QIEA will update the whole swarm by using random strategy. Experiments on the knapsack problem are compared with other evolutionary algorithms. The result indicates that the performance of new algorithm is superior to the others.
SSUES IN T ESTING OF S OFTWARE WITH NFR

Software Development has started experiencing the need of consideration of NFR (Non Functional Requirements) for producing high quality acceptable software. Mostly software engineering literature has considered only for testing Functional Requirements. In context of such a need this work attempts to consider NFR, resulting from quality concerns of stakeholder, along with their impact and effect on testing . We identify and bring out issues, in testing of NFR that warrant, purposeful and meaningful considerations.
Developing Aboveground Biomass Equations Both Compatible with Tree Volume Equations and Additive Systems for Single-Trees in Poplar Plantations in Jiangsu Province, China

We developed aboveground biomass equations for poplar plantations in Jiangsu Province, China, both compatible with tree volume equations and additive systems. Biomass equations were fitted with 80 selected and previously harvested sample trees. Additivity property was assured by applying a “controlling directly under total biomass proportion function” approach. Weighted regression was used to correct heteroscedasticity. Parameters were estimated using a nonlinear error-in-variable model. The results indicated that (1), on average, stems constituted the largest proportion (71.5%) of total aboveground biomass; (2) the aboveground biomass equations, both compatible with tree volume equations and additive systems, obtained good model fitting and prediction, of which the coefficient of determination ranged from 0.903 to 0.987, and the total relative error and the mean prediction error were less than 2.0% and 10.0%, respectively; (3) adding H and CW into the additive system of biomass equations did not improve model fitting and performance as expected, especially for branches and foliage biomass; and (4) the additive systems of biomass equations presented here provided more reliable and accurate biomass predictions than the independent biomass equations fitted by ordinary least square regression. This system of additive biomass equations will prove to be applicable for estimating biomass of poplar plantations in Jiangsu Province of China.
Prognostic role of translocator protein and oxidative stress markers in chronic lymphocytic leukemia patients treated with bendamustine plus rituximab

Principally located in the outer mitochondrial membrane, the translocator protein (TSPO) is an 18-kDa transmembrane protein that is a key component of the mitochondrial permeability transition pore. TSPO is associated with a number of biological processes, including apoptosis, the regulation of cellular proliferation, porphyrin transport and heme biosynthesis, immunomodulation, anion transport and the regulation of steroidogenesis. Thus, numerous studies have proposed TSPO as a promising target for novel therapeutic agents, particularly for the treatment of cancer. In the present study, the response of 30 consecutive chronic lymphocytic leukemia (CLL) patients to bendamustine and rituximab treatment was evaluated according to TSPO expression levels. Furthermore, thiobarbituric acid reactive substances (TBARS) and nitric oxide (NO) levels, as well as caspase-3 activity were determined. Compared with the lymphocytes of healthy donors, the 30 consecutive CLL patients exhibited increased TSPO expression levels, decreased TBARS and NO levels and reduced caspase-3 activity. Six months after the treatment commenced, the TSPO/mitochondria ratio resembled that of the healthy controls in 24/30 CLL patients. In addition, an increase in TBARS and NO levels, two markers of oxidative stress, and a potentiation of caspase-3 activity in all responder patients was observed. Notably, the six patients who appeared to be resistant to treatment also displayed higher TSPO levels, and lower caspase-3 activity and TBARS levels. These data indicate that TSPO expression may be a molecular prognostic factor in CLL patients.
Posttranslational Modifications Required for Cell Surface Localization and Function of the Fungal Adhesin Aga1p

ABSTRACT Adherence of fungal cells to host substrates and each other affects their access to nutrients, sexual conjugation, and survival in hosts. Adhesins are cell surface proteins that mediate these different cell adhesion interactions. In this study, we examine the in vivo functional requirements for specific posttranslational modifications to these proteins, including glycophosphatidylinositol (GPI) anchor addition and O-linked glycosylation. The processing of some fungal GPI anchors, creating links to cell wall β-1,6 glucans, is postulated to facilitate postsecretory traffic of proteins to cell wall domains conducive to their functions. By studying the yeast sexual adhesin subunit Aga1p, we found that deletion of its signal sequence for GPI addition eliminated its activity, while deletions of different internal domains had various effects on function. Substitution of the Aga1p GPI signal domain with those of other GPI-anchored proteins, a single transmembrane domain, or a cysteine capable of forming a disulfide all produced functional adhesins. A portion of the cellular pool of Aga1p was determined to be cell wall resident. Aga1p and the α-agglutinin Agα1p were shown to be under glycosylated in cells lacking the protein mannosyltransferase genes PMT1 and PMT2, with phenotypes manifested only in MATα cells for single mutants but in both cell types when both genes are absent. We conclude that posttranslational modifications to Aga1p are necessary for its biogenesis and activity. Our studies also suggest that in addition to GPI-glucan linkages, other cell surface anchorage mechanisms, such as transmembrane domains or disulfides, may be employed by fungal species to localize adhesins.
The Depreciating Dollar: Economic Effects and Policy Response

This report discusses the trend of depreciation of the dollar since 2002. This raises concern among some in Congress and the public that the dollar's decline is a symptom of broader economic problems, such as a weak economic recovery, rising public debt, and a diminished standing in the global economy. However, a falling currency is not always a problem, but possibly an element of economic adjustments that are, on balance, beneficial to the economy.
Fatal case of gas gangrene associated with intramuscular injections.

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