Miracle-dz/UniFAR-FTUs huggingface dataset:
Rethinking the Welfare Regime Approach

This article examines the potential value added by using a ‘welfare regime approach’ to explore welfare provision in low-income countries. Although the study of welfare regimes has traditionally focused on the welfare states of Organisation for Economic Co-operation and Development (OECD) countries, it has recently extended its purview to include ‘emerging’ welfare regimes in middle- and low-income countries, where the welfare state is considered to be absent. While conventional approaches use the welfare regimes of the ‘developed’ world as a starting point, the approach proposed here attempts to take into account the particularities of low-income countries like Bangladesh. This is done without assuming that high- and middle-income countries can teach us all that there is to know about welfare systems. In the Bangladesh context, the notion of a welfare regime provides a useful, yet problematic, conceptual apparatus for exploring the relationship between a welfare mix and its particular welfare, stratification and political mobilization outcomes. The article draws attention to the limited focus of the conventional approach on the central state–market nexus, leading to a lack of emphasis on family, kinship, community, local government and ‘civil society’ forms of welfare as well as those mediated by bilateral and global actors. It also draws attention to the wider range of relevant public welfare strategies that can be seen as functionally equivalent to social security in industrialized countries. The article ends by suggesting a research agenda combining an examination of the role of local, informal or customary strategies of managing welfare and insecurity on one hand and global or international strategies on the other.
Phenotypic Characterization of Insulin-Resistant and Insulin-Sensitive Obesity.

CONTEXT Whereas insulin resistance and obesity coexist, some obese individuals remain insulin sensitive. OBJECTIVE We examined phenotypic and metabolic factors associated with insulin sensitivity in both muscle and liver in obese individuals. DESIGN AND PARTICIPANTS Sixty-four nondiabetic obese adults (29 males) underwent hyperinsulinemic (15 and 80 mU/m(2) · min)-euglycemic clamps with deuterated glucose. Top tertile subjects for glucose infusion rate during the high-dose insulin clamp were assigned Musclesen and those in the lower two tertiles were assigned Muscleres. Secondarily, top tertile subjects for endogenous glucose production suppression during the low-dose insulin clamp were deemed Liversen and the remainder Liverres. MAIN OUTCOMES MEASURES Clinical and laboratory parameters and visceral, subcutaneous, liver, and pancreatic fat were compared. RESULTS Musclesen and Muscleres had similar body mass index and total fat (P > .16), but Musclesen had lower glycated hemoglobin (P < .001) and systolic (P = .01) and diastolic (P = .03) blood pressure (BP). Despite similar sc fat (P = 1), Musclesen had lower visceral (P < .001) and liver (P < .001) fat. Liversen had lower visceral (P < .01) and liver (P < .01) fat and C-reactive protein (P = .02) than Liverres. When subjects were grouped by both glucose infusion rate during the high-dose insulin clamp and endogenous glucose production suppression, insulin sensitivity at either muscle or liver conferred apparent protection from the adverse metabolic features that characterized subjects insulin resistant at both sites. High-density lipoprotein-cholesterol, 1-hour glucose, systolic BP, and triglycerides explained 54% of the variance in muscle insulin sensitivity. CONCLUSIONS Obese subjects who were insulin sensitive at muscle and/or liver exhibited favorable metabolic features, including lower BP, liver and visceral adiposity. This study identifies factors associated with, and possibly contributing to, insulin sensitivity in obesity.
Paroxetine and fluoxetine effects on mood and cognitive functions in depressed nondemented elderly patients.

BACKGROUND A large proportion of the elderly population complains of depressive symptoms. The ideal antidepressant for these patients, who often suffer from numerous concomitant diseases, should not worsen their cognitive functions and should be free of contraindications. METHOD To assess the effects of 2 selective serotonin reuptake inhibitors on cognitive functions in elderly depressed patients (ICD-10 criteria), we conducted a double-blind, randomized, parallel-group, multicenter study comparing paroxetine (20-40 mg daily) and fluoxetine (20-60 mg daily) treatment for 1 year. Cognitive performance was evaluated by means of the Buschke Selective Reminding Test, the Blessed Information and Memory Test, the Clifton Assessment Schedule, the Cancellation Task Test, and the Wechsler Paired Word Test; the Hamilton Rating Scale for Depression (HAM-D) and the Clinical Anxiety Scale were administered to assess the course of depressive and anxiety symptoms, respectively. RESULTS 242 patients were enrolled (mean +/- SD age = 75.4 +/- 6.6 years). During the study, no deterioration of cognition was observed; on the contrary, most of the tested cognitive functions improved. Good antidepressant efficacy was maintained for over 1 year with both drugs, based on the percentage of responders to treatment (patients achieving a HAM-D total score < 10; 60%). Both drugs showed a good tolerability and safety profile. CONCLUSION The 2 antidepressants proved to be suitable for the long-term treatment of depression in the elderly and to be devoid of detrimental effects on the tested cognitive functions.
Assessing Tail Dependence in Electricity Markets

Tail dependence characterizes cross market linkages during periods of extreme price behavior. Analyzing tail dependence can richly inform market participants, in particular those operating across several markets how to understand price risk. A copula approach is therefore employed to assess the tail dependence across regional electricity markets. We use daily data from five Australia's regional electricity markets (Queensland, New South Wales, Victoria, South Australia and Tasmania). We find significant tail dependence between wholesale electricity prices indicating that especially extreme price observations like price spikes tend to occur jointly across these markets. Our results provide market participants with more timely suggestions for effective risk management and hedging strategies.
Competitive intelligence skills needed in South Africa

South Africa as a country continues to rank low in the world of competitiveness. The research done for this dissertation focused on the need for South African organisations to perceive Competitive Intelligence (CI) as one of the most important tools to improve their competitiveness through a systematic, practical approach to make the CI cycle worth while, especially through skills development. This study intends to identify the skills CI professionals in South Africa need in order to conduct the CI process in organisations effectively, thereby improving the country’s competitive position. However, the difficulty of this task lies with organisations in general not acknowledging the necessity of CI in the workplace. Only a limited number of organisations recognise the importance of such a unit. A survey was therefore conducted, by questionnaire, among organisations with existing CI units in which the respondents had to identify the skills they deemed necessary for the CI professional to run the CI process effectively. Findings suggested that the majority of respondents were 40 years and older, in the top structure of larger organisations and had been using CI for longer than five years. The overwhelming result is thus that there are skills inequalities between what skills respondents view as crucial and those that rated highest in their self-evaluation. Skills identified as most important include, among others, networking and research skills analytical abilities. The research also indicated that where CI had been established in certain organisations for at least five years, it did not reflect positively overall on South Africa’s current competitive situation. However, where there is a systematic CI approach, problem-solving is easier to address and negatives could be turned around. With this in mind and a proper “buy-in” into skills development, it will have a very positive outcome for all the organisations that wish to improve their competitiveness.
Multi-Period Dea Incentive Regulation in Electricity Distribution

Multi-period multi-product regulatory schemes for electricity distributors are presented, based on cost information from a productivity analysis model and an agency theoretical decision model. The proposed schemes are operational and demonstrate considerable advantages compared to the popular CPI-X revenue cap regulation. The schemes avoid arbitrariness, too high or negative informational rents as well as ratchet effects and they promote rapid productivity catch-up by making full use of available data. More generally, the paper contributes to the theoretical unification between firm-based Data Envelopment Analysis (DEA) productivity models and micro-economic reimbursement theories.
A Generalized Additive Model For Microarray Gene Expression Data Analysis

Abstract Microarray technology allows the measurement of expression levels of a large number of genes simultaneously. There are inherent biases in microarray data generated from an experiment. Various statistical methods have been proposed for data normalization and data analysis. This paper proposes a generalized additive model for the analysis of gene expression data. This model consists of two sub-models: a non-linear model and a linear model. We propose a two-step normalization algorithm to fit the two sub-models sequentially. The first step involves a non-parametric regression using lowess fits to adjust for non-linear systematic biases. The second step uses a linear ANOVA model to estimate the remaining effects including the interaction effect of genes and treatments, the effect of interest in a study. The proposed model is a generalization of the ANOVA model for microarray data analysis. We show correspondences between the lowess fit and the ANOVA model methods. The normalization procedure does not assume the majority of genes do not change their expression levels, and neither does it assume two channel intensities from the same spot are independent. The procedure can be applied to either one channel or two channel data from the experiments with multiple treatments or multiple nuisance factors. Two toxicogenomic experiment data sets and a simulated data set are used to contrast the proposed method with the commonly known lowess fit and ANOVA methods.
Does Substance Use Affect Reliabilities of the Implicit Association Test?

The authors examined whether use of alcohol or marijuana affected reliability of the Implicit Association Test (IAT; A. G. Greenwald, D. E. McGhee, & J. L. K. Schwartz, 1998). Consistent with research indicating the possibility that marijuana use depletes cognitive resources, the authors found worse reliabilities for participants who recently used marijuana than for those who had not. Recent alcohol users and nonusers demonstrated similar IAT reliability. Subsequent analyses indicated that reliability differences between marijuana users and nonusers were most pronounced when participants began with incongruous tasks and then switched to congruous tasks. Results were consistent with work on the residual costs of task switching that indicates that effortful tasks promote interference with tasks that follow. The authors discussed results in terms of IAT scoring procedures and the prevalence of use of alcohol and marijuana on university campuses.
Molecular and epidemiological study on nosocomial transmission of HCV in hemodialysis patients in Brazil

An epidemiological and molecular study of hepatitis C virus (HCV) infection was carried out in Brazilian hemodialysis centers. A total of 1,095 patients in all 15 hemodialysis centers in the State of Goiás, Brazil, were studied. All patients were interviewed for possible risk factors to HCV infection and serum samples tested for anti‐HCV by ELISA and for HCV RNA by nested RT‐PCR of the 5′ NC region. For sequence analysis, HCV RNA amplification for the NS5B region (nt 8,279–8,619) was performed. The phylogenetic tree was generated with MrBayes, and clusters with support values above 0.85 were considered epidemiologically related. Of the 1,095 patients, 180 were anti‐HCV and/or HCV RNA positive, resulting in an overall prevalence of 16.4% (95% CI: 14.3–18.7). The prevalence of HCV infection in the dialysis centers ranged from 0% to 47.7%. Multivariate analysis of risk factors revealed that history of blood transfusion not screened for anti‐HCV and length of time on hemodialysis were independently associated with HCV infection in this population. One hundred six samples could be amplified and sequenced in the NS5B region. Among them, plylogenetic tree analysis revealed that 69 sequences form 13 separated clusters, which were supported by credibility intervals ranging from 85% to 100%, indicating a very close relationship among the HCV isolates and therefore a likely transmission of the virus between patients. By combining phylogenetic analysis with epidemiological data, routes of transmission between the clustered‐related‐patients could be suggested. These findings provide evidence for nosocomial transmission of HCV in Brazilian hemodialysis centers. J. Med. Virol. 79:1325–1333, 2007. © Wiley‐Liss, Inc.
Does Homeownership Affect Child Outcomes

We study the impact of homeowning on the cognitive and behavioral outcomes of children. Using four waves of a comprehensive national panel data set, we control for many social, demographic and economic variables previously found to influence child outcomes. The data are a panel, allowing us to control for unobserved household- and child-specific factors. We use a treatment effects model to address the issue of possible sample selection bias caused by unobserved variables that influence both the parent's choice of whether to own or rent and whether to invest in their children. We find that owning a home compared with renting leads to a 13 to 23% higher quality home environment, greater cognitive ability and fewer child behavior problems. For children living in owned homes, math achievement is up to 9% higher, reading achievement is up to 7% higher, and children's behavioral problems are 1 to 3% lower. Copyright 2002 American Real Estate and Urban Economics Association.
Ambiguity in asset pricing and portfolio choice: a review of the literature

We survey the literature that has explored the implications of decision-making under ambiguity for financial market outcomes, such as portfolio choice and equilibrium asset prices. This ambiguity literature has led to a number of significant advances in our ability to rationalize empirical features of asset returns and portfolio decisions, such as the failure of the two-fund separation theorem in portfolio decisions, the modest exposure to risky securities observed for a majority of investors, the home equity preference in international portfolio diversification, the excess volatility of asset returns, the equity premium and the risk-free rate puzzles, and the occurrence of trading break-downs.
A Network Perspective for a Borderless International Structure: The Experience of an Italian Entrepreneurial SME in Morocco

Going global has become more than just a strategy; it is essential to ensuring revenues and firm survival, especially for organizations that function in saturated, highly competitive markets. Because small firms often lack the internal resources, competencies, information, capital, and managerial experience needed to expand globally, they tend to rely on resources held by other, partner firms. Thus, a network view that encourages resource and information sharing among participants can help smaller firms overcome any limitations stemming from a lack of internal resources. The experience of an Italian manufacturer with operations in Morocco reflects a new approach to network formation that focuses particularly on the learning process and acquisition of knowledge in local markets. © 2013 Wiley Periodicals, Inc.
Sale-and-leaseback as a British Real Estate Model

Purpose – Many established trading companies have had considerable capital value locked into their operational properties. These properties have been identified as producing lower returns on invested capital than core business activities. Consequently, there has been a growing trend for the splitting of operational property from core business activity. This paper seeks to identify trends in sale‐and‐leaseback, which is the most common model in the UK.Design/methodology/approach – This paper reviews, the existing literature and some past transactions in order to identify the motivations of both operational businesses and property investors in adopting the model. Some transaction case studies are also highlighted.Findings – Identification of the motives behind this approach. Accounting, taxation and capital release are identified as the main drivers when the model first became widespread in the UK two decades ago. It is now driven by taxation and capital release. Originally adopted by leading companies, sal.
On the relationship between the MoM and the GMT [EM theory]

The method of moments (MoM) is compared with the generalized multipole technique (GMT), which has been shown to be very efficient. Although the GMT can be considered to be a variant of the MoM, it is based on a completely different philosophical foundation. Both the foundation and concrete implementations are considered. It is shown how the MMP code, based on the GMT, can profit from MoM concepts, and how MoM codes can profit from GMT ideas. <<ETX>>
Human IgA-binding Peptides Selected from Random Peptide Libraries

Background: Pharmaceutical application of human IgA requires a highly specific IgA purification system. Results: A peptide affinity ligand for IgA was designed and optimized for affinity/specificity using randomized phage libraries and mutational studies. Conclusion: The designed IgA-binding peptide has high affinity and specificity for human IgA. Significance: This IgA-binding peptide can be used for specific purification of human IgA. Phage display system is a powerful tool to design specific ligands for target molecules. Here, we used disulfide-constrained random peptide libraries constructed with the T7 phage display system to isolate peptides specific to human IgA. The binding clones (A1–A4) isolated by biopanning exhibited clear specificity to human IgA, but the synthetic peptide derived from the A2 clone exhibited a low specificity/affinity (Kd = 1.3 μm). Therefore, we tried to improve the peptide using a partial randomized phage display library and mutational studies on the synthetic peptides. The designed Opt-1 peptide exhibited a 39-fold higher affinity (Kd = 33 nm) than the A2 peptide. An Opt-1 peptide-conjugated column was used to purify IgA from human plasma. However, the recovered IgA fraction was contaminated with other proteins, indicating nonspecific binding. To design a peptide with increased binding specificity, we examined the structural features of Opt-1 and the Opt-1-IgA complex using all-atom molecular dynamics simulations with explicit water. The simulation results revealed that the Opt-1 peptide displayed partial helicity in the N-terminal region and possessed a hydrophobic cluster that played a significant role in tight binding with IgA-Fc. However, these hydrophobic residues of Opt-1 may contribute to nonspecific binding with other proteins. To increase binding specificity, we introduced several mutations in the hydrophobic residues of Opt-1. The resultant Opt-3 peptide exhibited high specificity and high binding affinity for IgA, leading to successful isolation of IgA without contamination.
Characterization of Schizosaccharomyces pombeHus1: a PCNA-Related Protein That Associates with Rad1 and Rad9

ABSTRACT Hus1 is one of six checkpoint Rad proteins required for allSchizosaccharomyces pombe DNA integrity checkpoints. MYC-tagged Hus1 reveals four discrete forms. The main form, Hus1-B, participates in a protein complex with Rad9 and Rad1, consistent with reports that Rad1-Hus1 immunoprecipitation is dependent on the rad9 + locus. A small proportion of Hus1-B is intrinsically phosphorylated in undamaged cells and more becomes phosphorylated after irradiation. Hus1-B phosphorylation is not increased in cells blocked in early S phase with hydroxyurea unless exposure is prolonged. The Rad1–Rad9–Hus1-B complex is readily detectable, but upon cofractionation of soluble extracts, the majority of each protein is not present in this complex. Indirect immunofluorescence demonstrates that Hus1 is nuclear and that this localization depends on Rad17. We show that Rad17 defines a distinct protein complex in soluble extracts that is separate from Rad1, Rad9, and Hus1. However, two-hybrid interaction, in vitro association and in vivo overexpression experiments suggest a transient interaction between Rad1 and Rad17.
Sliding window energy detection for spectrum sensing under low SNR conditions

For spectrum sensing, energy detection has the advantages of low complexity, rapid analysis, and requires no knowledge of the transmission signal, which makes it suitable for a wide range of applications. However, under low signal-to-noise ratio conditions, the required window length or the time-bandwidth product for energy detection to achieve a desired detection performance is large. In addition, conventional energy detection assumes that the detection tests are independent, that is, there is no overlap between individual detection tests. These properties significantly reduce the detection speed when energy detection is used for the continuous monitoring over a communication channel for the detection of signal transmission activities. In this paper, we propose a sliding window detection analysis with overlap among multiple tests. Algorithms for effective performance analysis of the proposed sliding window energy detection are proposed. The impact of window length on distribution of detection time is investigated. Simulation results on the proposed sliding window energy detection are also compared with the theoretically predicted and conventional energy detection performance estimates. Copyright © 2015 John Wiley & Sons, Ltd.
A Model of Momentum

Optimal investment of firms implies that expected stock returns are tied with the expected marginal benefit of investment divided by the marginal cost of investment. Winners have higher expected growth and expected marginal productivity (two major components of the marginal benefit of investment), and earn higher expected stock returns than losers. The investment model succeeds in capturing average momentum profits, reversal of momentum in long horizons, as well as the interaction of momentum with market capitalization, firm age, trading volume, and stock return volatility. However, the model fails to reproduce procyclical momentum profits.