Miracle-dz/UniFAR-FTUs huggingface dataset:
Laminin 332 processing impacts cellular behavior

Laminin 332, composed of the α3, β3 and γ2 chains, is an epithelial-basement membrane specific laminin variant. Its main role in normal tissues is the maintenance of epithelial-mesenchymal cohesion in tissues exposed to external forces, including skin and stratified squamous mucosa. After being secreted and deposited in the extracellular matrix, laminin 332 undergoes physiological maturation processes consisting in the proteolytic processing of domains located within the α3 and the γ2 chains. These maturation events are essential for laminin 332 integration into the basement membrane where it plays an important function in the nucleation and maintenance of anchoring structures. Studies in normal and pathological situations have revealed that laminin 332 can trigger distinct cellular events depending on the level of its proteolytic cleavages. In this review, the biological and structural characteristics of laminin 332 domains are presented and we discuss whether they trigger specific functions.
Crises in Emerging Market Economies: A Global Perspective

The paper argues that global financial factors played an important role in the capital-inflow episode in Emerging Market economies (EMs), during the early part of the 1990s, and clearly in the Sudden Stop (of capital inflows) crises that took place after the 1998 Russian crisis. Moreover, the paper shows that recovery after crises that exhibit large output loss (more than 5 percent of GDP from peak to trough) occurs in a Phoenix-like fashion: little credit or investment is required. These results strongly suggest that: (1) deep financial crises can be prevented or at least largely alleviated and (2) global institutions and arrangements should be high on the policy agenda. The paper then discusses an Emerging Market Fund (EMF) charged with the task of lowering the incidence of contagion in EM bond prices. In addition, the paper analyzes domestic policies and concludes that they are critical and important in making EMs less vulnerable to shocks but are unlikely to succeed in fully shielding these economies from global financial shocks if not supported by arrangements like the EMF. Finally, two sections of the paper are devoted to discussing some current issues regarding applicable theory and econometrics.
Supervisory Board Composition Effects On Islamic Banks ’ Risk-Taking Behavior

Islamic banks underlie the fundamental principles of the Shari’ah, which encompass all business activities, financial contracts, and transactions. The Shari’ah Supervisory Board (SSB) monitors and certifies compliancy and is unique to the governance structure of Islamic banks compared to their Western counterparts. This study addresses the question of how the compositional characteristics of the SSB influence the loan portfolio risk-taking of Islamic banks. As such, we analyze to which degree the legal supervisory functions of a SSB affect the banks’ risk-taking behavior. Over the period from 2000 to 2010, we regard cross-country bank-level data from the Middle East and Northern Africa as well as from Southeast Asia. Our results reveal evidence that the loan portfolio risk-taking of Islamic banks is positively influenced by increasing size of the SSB, as well as when top ranked Shari’ah scholars with multiple memberships have board mandates and when annual changes occur in the composition of a SSB, regarding particularly previous period variables with second lags. We find that supervisory effectiveness and disciplining power of individual bank SSBs towards the risk-taking in the loan portfolio of Islamic banks decreases in a decentralized Shari’ah-compliant governance structure. The reverse causality analysis shows strongly that SSB factors affect primarily loan portfolio risk-taking, not the other way around.
Investigating Haze-Relevant Features in a Learning Framework for Image Dehazing

Haze is one of the major factors that degrade outdoor images. Removing haze from a single image is known to be severely ill-posed, and assumptions made in previous methods do not hold in many situations. In this paper, we systematically investigate different haze-relevant features in a learning framework to identify the best feature combination for image dehazing. We show that the dark-channel feature is the most informative one for this task, which confirms the observation of He et al. [8] from a learning perspective, while other haze-relevant features also contribute significantly in a complementary way. We also find that surprisingly, the synthetic hazy image patches we use for feature investigation serve well as training data for realworld images, which allows us to train specific models for specific applications. Experiment results demonstrate that the proposed algorithm outperforms state-of-the-art methods on both synthetic and real-world datasets.
Option Pricing Formulae using Fourier Transform : Theory and Application

Fourier transform techniques are playing an increasingly important role in Mathematical Finance. For arbitrary stochastic price processes for which the characteristic functions are tractable either analytically or numerically, prices for a wide range of derivatives contracts are readily available by means of Fourier inversion methods. In this paper we $rst review the convenient mathematical properties of Fourier transforms and characteristic functions, survey the most popular pricing algorithms and finally compare numerical quadratures for the evaluation of density functions and option prices. At the end, we discuss practical implementation details and possible re$nements with respect to computational e%ciency.
Automation, Algorithms, and Politics| Automation, Big Data and Politics: A Research Review

We review the great variety of critical scholarship on algorithms, automation, and big data in areas of contemporary life both to document where there has been robust scholarship and to contribute to existing scholarship by identifying gaps in our research agenda. We identify five domains with opportunities for further scholarship: (a) China, (b) international interference in democratic politics, (c) civic engagement in Latin American, (d) public services, and (e) national security and foreign affairs. We argue that the time is right to match dedication to critical theory of algorithmic communication with a dedication to empirical research through audit studies, network ethnography, and investigation of the political economy of algorithmic production.
Computational models of the Posner simple and choice reaction time tasks

The landmark experiments by Posner in the late 1970s have shown that reaction time (RT) is faster when the stimulus appears in an expected location, as indicated by a cue; since then, the so-called Posner task has been considered a “gold standard” test of spatial attention. It is thus fundamental to understand the neural mechanisms involved in performing it. To this end, we have developed a Bayesian detection system and small integrate-and-fire neural networks, which modeled sensory and motor circuits, respectively, and optimized them to perform the Posner task under different cue type proportions and noise levels. In doing so, main findings of experimental research on RT were replicated: the relative frequency effect, suboptimal RTs and significant error rates due to noise and invalid cues, slower RT for choice RT tasks than for simple RT tasks, fastest RTs for valid cues and slowest RTs for invalid cues. Analysis of the optimized systems revealed that the employed mechanisms were consistent with related findings in neurophysiology. Our models predict that (1) the results of a Posner task may be affected by the relative frequency of valid and neutral trials, (2) in simple RT tasks, input from multiple locations are added together to compose a stronger signal, and (3) the cue affects motor circuits more strongly in choice RT tasks than in simple RT tasks. In discussing the computational demands of the Posner task, attention has often been described as a filter that protects the nervous system, whose capacity is limited, from information overload. Our models, however, reveal that the main problems that must be overcome to perform the Posner task effectively are distinguishing signal from external noise and selecting the appropriate response in the presence of internal noise.
The Background of Reduced Face Specificity of N170 in Congenital Prosopagnosia

Congenital prosopagnosia is lifelong face-recognition impairment in the absence of evidence for structural brain damage. To study the neural correlates of congenital prosopagnosia, we measured the face-sensitive N170 component of the event-related potential in three members of the same family (father (56 y), son (25 y) and daughter (22 y)) and in age-matched neurotypical participants (young controls: n = 14; 24.5 y±2.1; old controls: n = 6; 57.3 y±5.4). To compare the face sensitivity of N170 in congenital prosopagnosic and neurotypical participants we measured the event-related potentials for faces and phase-scrambled random noise stimuli. In neurotypicals we found significantly larger N170 amplitude for faces compared to noise stimuli, reflecting normal early face processing. The congenital prosopagnosic participants, by contrast, showed reduced face sensitivity of the N170, and this was due to a larger than normal noise-elicited N170, rather than to a smaller face-elicited N170. Interestingly, single-trial analysis revealed that the lack of face sensitivity in congenital prosopagnosia is related to a larger oscillatory power and phase-locking in the theta frequency-band (4–7 Hz, 130–190 ms) as well as to a lower intertrial jitter of the response latency for the noise stimuli. Altogether, these results suggest that congenital prosopagnosia is due to the deficit of early, structural encoding steps of face perception in filtering between face and non-face stimuli.
Minimally Invasive Periodontal Treatment Using the Er,Cr: YSGG Laser. A 2-year Retrospective Preliminary Clinical Study

Minimally invasive surgery (MIS) using the erbium, chromium: yttrium-scandium-gallium-garnet (Er,Cr:YSGG) laser (Waterlase MD, Biolase, Irvine, CA) to treat moderate to advanced periodontal disease is presented as an alternative to conventional therapies. To date, there are few short- or long-term studies to demonstrate the effects of this laser in treating and maintaining periodontal health. Electronic clinical records from 16 patients – total of 126 teeth, with pocket depths ranging from 4 mm to 9 mm – were treated with the same protocol using the Er,Cr:YSGG laser. The mean baseline probing depths (PD) were 5 mm and clinical attachment levels (CAL) were 5 mm in the 4 - 6 mm pretreated laser group. The mean baseline probing depths were 7.5 and 7.6 mm for PD and CAL respectfully in the 7 – 9 mm pretreatment laser group. At the 2 year mark, the average PD was 3.2 ± 1.1 mm for the 4-6 mm pocket group and the 7-9 mm pocket group had a mean PD of 3.7 ± 1.2 mm. mean CAL was 3.1 ± 1.1 mm for the 4-6 mm group and 3.6 ± 1.2 for the 7-9 mm group with an overall reduction of 1.9 mm and 4.0 mm respectively. At one and two years, both groups remained stable with PD comparable to the three-month gains. The CAL measurements at one and two years were also comparable to the three-month gains.
Pricing Online Decisions: Beyond Auctions

We consider dynamic pricing schemes in online settings where selfish agents generate online events. Previous work on online mechanisms has dealt almost entirely with the goal of maximizing social welfare or revenue in an auction settings. This paper deals with quite general settings and minimizing social costs. We show that appropriately computed posted prices allow one to achieve essentially the same performance as the best online algorithm. This holds in a wide variety of settings. Unlike online algorithms that learn about the event, and then make enforcable decisions, prices are posted without knowing the future events or even the current event, and are thus inherently dominant strategy incentive compatible. In particular we show that one can give efficient posted price mechanisms for metrical task systems, some instances of the k-server problem, and metrical matching problems. We give both deterministic and randomized algorithms. Such posted price mechanisms decrease the social cost dramatically over selfish behavior where no decision incurs a charge. One alluring application of this is reducing the social cost of free parking exponentially.
Set-size effects for sampled shapes: experiments and model

The location of imperfections or heterogeneities in shapes and contours often correlates with points of interest in a visual scene. Investigating the detection of such heterogeneities provides clues as to the mechanisms processing simple shapes and contours. We determined set-size effects (e.g., sensitivity to single target detection as distractor number increases) for sampled contours to investigate how the visual system combines information across space. Stimuli were shapes sampled by oriented Gabor patches: circles and high-amplitude RF4 and RF8 radial frequency patterns with Gabor orientations tangential to the shape. Subjects had to detect a deviation in orientation of one element (“heterogeneity”). Heterogeneity detection sensitivity was measured for a range (7–40) of equally spaced (2.3–0.4°) elements. In a second condition, performance was measured when elements sampled a part of the shapes. We either varied partial contour length for a fixed (7) set-size, co-varying inter-element spacing, or set-size for a fixed spacing (0.7°), co-varying partial contour length. Surprisingly, set-size effects (poorer performance with more elements) are rarely seen. Set-size effects only occur for shapes containing concavities (RF4 and RF8) and when spacing is fixed. When elements are regularly spaced, detection performance improves with set-size for all shapes. When set-size is fixed and spacing varied, performance improves with decreasing spacing. Thus, when an increase in set-size and a decrease in spacing co-occur, the effect of spacing dominates, suggesting that inter-element spacing, not set-size, is the critical parameter for sampled shapes. We propose a model for the processing of simple shapes based on V4 curvature units with late noise, incorporating spacing, average shape curvature, and the number of segments with constant sign of curvature contained in the shape, which accurately accounts for our experimental results, making testable predictions for a variety of simple shapes.
Followership: A Classroom Exercise to Introduce the Concept

Followership is valuable for personal and organizational success, whether success is measured by satisfaction with work, improved team relationships, obtaining promotions, or quality and quantity of work output. Furthermore, senior executives and coaches recognize it as a critical skill. Despite this, creating effective followership training in the classroom is challenging because of media messages that preference leadership, internal schemas held by students that ignore followership, and cultural biases against it. This article presents a memorable kinaesthetic, visual classroom activity that introduces followership in a theory-agnostic way. The exercise begins with students introducing each other as leaders or followers, and then debriefing that activity using the Describe, Analyze, and Evaluate methodology from multicultural training. Over a 10-year period, the exercise has successfully engaged undergraduate and graduate students, MBA candidates, and working professionals from frontline to senior management.
The Effect of Bortezomib on Antibody-Mediated Rejection after Kidney Transplantation

Purpose Recently, bortezomib has been used to treat antibody-mediated rejection (AMR) refractory to conventional treatment such as plasmapheresis, intravenous immunoglobulin, and rituximab. The authors aimed to describe their experiences when bortezomib was used to treat refractory AMR. Materials and Methods Eleven refractory AMR episodes treated with bortezomib were included in this study. The patients received one or two cycles of bortezomib (1.3 mg/m2) on days 1, 4, 8, and 11. Results Bortezomib effectively reduced antibodies against various targets, including human leukocyte antigen (HLA) class I and II, ABO blood group antigen, and angiotensin II type 1 receptor. Antibodies were depleted or reduced significantly in eight AMR episodes. Overall, there was a significant improvement in the mean estimated glomerular filtration rate (eGFR) at 3 months after therapy (36.91±22.15 mL/min/1.73 m2) versus eGFR at time of AMR diagnosis (17.00±9.25 mL/min/1.73 m2; p=0.007). All six early-onset AMR episodes (within 6 months post-transplantation) showed full recovery of allograft function. Additionally, three of the five late-onset AMR episodes (>6 months post-transplantation) showed improved allograft function. Conclusion Anti-humoral treatment based on bortezomib might be an effective strategy against refractory AMR caused by various types of antibodies. Notably, this treatment could be more effective in early-onset AMR than in late-onset AMR.
ead-induced alteration of apoptotic proteins in different regions of dult rat brain

In our earlier investigations, we have demonstrated the alteration of antioxidant enzymes in adult rat brain exposed to lead. This study was carried out to investigate the effect of lead on inducing apoptosis by choosing poly (ADP-ribose) polymerase (PARP), bcl-2 and caspase-3 expression as marker proteins in the cerebellum, the hippocampus, the brain stem and the frontal cortex. Adult male rats were treated with lead acetate (500 ppm) through drinking water for a period of 8 weeks and parallel controls were eywords: ead toxicity poptotic cell death xidative stress rain maintained on sodium acetate. Both control and exposed rats were sacrificed at intervals of 4 and 8 weeks, brains were isolated and different regions namely the cerebellum, the hippocampus, the frontal cortex and the brain stem were separated and processed to investigate PARP, bcl-2 and caspase-3 expression using western blotting. The results suggest that lead induces region-specific response of expression in apoptotic proteins of rat brain showing more effect in hippocampus and cerebellum and less effect in frontal cortex sue s ellum o D s r l e d s i s 2 o t c a 2 t and brain stem and it is tis in hippocampus and cereb
Computing Curricula: Teaching Theory of Science to Computer Science Students

An ideal Science for the existing Theory of Science (Popper, Carnap, Kuhn, Chalmers) is Physics. Not many modern Sciences conform to that ideal, however. Philosophy of Science (Theory of Science) as it is today is not of much help when trying to understand e.g. Computer Science. There is an urgent need to broaden the Theory of Science perspective in order to match the present situation within the area, as well as to help its further development. Computer Science has its basis in Logic and Mathematics, and in many cases its theoretical and experimental research methods follow patterns of classical scientific fields of Logic/Mathematics and Natural Sciences. On the other hand, computer modeling and simulation which is specific for the discipline and it is rapidly growing in importance, applied to computers, as well as to other scientific and artistic fields, hardly corresponds to traditional definition of scientific method. Situation gets even more complicated in the field of Intelligent Systems (Artificial Intelligence, AI). AI is generally associated with Computer Science, but it has many important links with other fields such as Mathematics, Psychology, Cognition, Biology, Behavioral and Brain Sciences, Linguistics and Philosophy, among others. This paper addresses the need for paradigm shift within Theory of Science. It shows that it is essential for students of Computer Science to not only acquire the concepts from Theory of Science within its conventional domain, but also widen the perspective and see the field in its context of other scientific traditions.
Errorless learning in dementia

Errorless learning (EL) is a principle used to teach new information or skills to people with cognitive impairment. In people with dementia, EL principles have mostly been studied in laboratory tasks that have little practical relevance for the participants concerned, yet show positive effects. This is the first paper to exclusively review the literature concerning the effects of EL on the performance of useful everyday tasks in people with dementia. The role of factors such as type of dementia, type of task, training intensity, EL elements, outcome measures, quality of experimental design, and follow-up are discussed. The results indicate that, compared with errorful learning (EF) or no treatment, EL is more effective in teaching adults with dementia a variety of meaningful daily tasks or skills, with gains being generally maintained at follow-up. The effectiveness of EL is highly relevant for clinical practice because it shows that individuals with dementia are still able to acquire meaningful skills and engage in worthwhile activities, which may potentially increase their autonomy and independence, and ultimately their quality of life, as well as reduce caregiver burden and professional dependency. Suggestions for future research are given, along with recommendations for effective EL-based training programs, with the aim of developing a clinical manual for professionals working in dementia care.
Nonlinear associations between job insecurity and adaptive performance: The mediating role of negative affect and negative work reflection

ABSTRACT This study aimed at investigating the association between employee-rated job insecurity and supervisor-rated adaptive performance. We hypothesized a nonlinear association between job insecurity and adaptive performance, expecting negative affect and negative work reflections to mediate this relationship. Using a sample of 131 employee–supervisor dyads, path analysis revealed a curvilinear relation between job insecurity and supervisor-rated adaptive performance, indicating medium job insecurity being linked to the lowest adaptive performance. Bootstrapping confirmed that negative affect and negative work reflection both mediated the nonlinear association between job insecurity and adaptive performance. After a time lag of 16 weeks, 71 supervisors again rated their employees’ adaptive performance. Path analysis confirmed a nonlinear association between employees’ job insecurity (T1) and supervisor-rated adaptive performance (T2). Theoretical and practical implications are discussed.
Investigating the protective properties of milk phospholipids against ultraviolet light exposure in a skin equivalent model

Current research on bioactive molecules in milk has documented health advantages of bovine milk and its components. Milk Phospholipids, selected for this study, represent molecules with great potential benefit in human health and nutrition. In this study we used confocal reflectance and multiphoton microscopy to monitor changes in skin morphology upon skin exposure to ultraviolet light and evaluate the potential of milk phospholipids in preventing photodamage to skin equivalent models. The results suggest that milk phospholipids act upon skin cells in a protective manner against the effect of ultraviolet (UV) radiation. Similar results were obtained from MTT tissue viability assay and histology.