Miracle-dz/UniFAR-FTUs huggingface dataset:
Opsin1-2, Gqα and arrestin levels at Limulus rhabdoms are controlled by diurnal light and a circadian clock

SUMMARY Dark and light adaptation in photoreceptors involve multiple processes including those that change protein concentrations at photosensitive membranes. Light- and dark-adaptive changes in protein levels at rhabdoms have been described in detail in white-eyed Drosophila maintained under artificial light. Here we tested whether protein levels at rhabdoms change significantly in the highly pigmented lateral eyes of wild-caught Limulus polyphemus maintained in natural diurnal illumination and whether these changes are under circadian control. We found that rhabdomeral levels of opsins (Ops1-2), the G protein activated by rhodopsin (Gqα) and arrestin change significantly from day to night and that nighttime levels of each protein at rhabdoms are significantly influenced by signals from the animal's central circadian clock. Clock input at night increases Ops1-2 and Gqα and decreases arrestin levels at rhabdoms. Clock input is also required for a rapid decrease in rhabdomeral Ops1-2 beginning at sunrise. We found further that dark adaptation during the day and the night are not equivalent. During daytime dark adaptation, when clock input is silent, the increase of Ops1-2 at rhabdoms is small and Gqα levels do not increase. However, increases in Ops1-2 and Gqα at rhabdoms are enhanced during daytime dark adaptation by treatments that elevate cAMP in photoreceptors, suggesting that the clock influences dark-adaptive increases in Ops1-2 and Gqα at Limulus rhabdoms by activating cAMP-dependent processes. The circadian regulation of Ops1-2 and Gqα levels at rhabdoms probably has a dual role: to increase retinal sensitivity at night and to protect photoreceptors from light damage during the day.
Political economy of panchayats in South India

Based on a study of some 500 villages in the four southern Indian states of Andhra Pradesh, Karnataka, Kerala and Tamil Nadu, this paper examines how the functioning of the panchayat system mandated by the 73rd amendment to the Constitution has had an impact on the economic status of villages and the households within them. The study finds that gram panchayats, created by this massive experiment in democratic decentralisation, have had an effect on the delivery of public services, for example, in the targeting of beneficiaries of welfare programmes, but also that positive outcomes are linked to the political elites thrown up by the system.
Challenges in Teaching Pupils with Visual Impairment in Inclusive Classrooms: The Experience of Ghanaian Teachers

The study sought to investigate the teachers’challenges in teaching pupils with visual impairment in inclusive classrooms in Ghana. A sample of 59 teachers was chosen, representing 3 inclusive basic schools. A questionnaire was administered on the teachers. The study revealed that teachers have challenges in teaching pupils with visual impairment. Challenges on classroom size,available material and even known-how on their operation with such pupils. Teachers further agreed that they have some assistive device but the majority of devices are not provided to ease the teaching of the visually impaired pupil. Based on the findings, Teachers need in-service training in the use of Braille and large print material so that children with visual impairment can be effectivelyincluded in the ordinary school. Added to that, the government of Ghana should improve supply of teaching and learning materials Brailled textbooks as well as assistive devices. Keywords: Challenges, Teachers, Visual impairment, Inclusive classroom
The Challenge of Producing and Marketing Colloidal Silver Water Filters in Nepal

Background: Obtaining safe drinking water can be a challenge in Nepal. By training potters and setting up production sites for Colloidal Silver Filters, several non-governmental organizations have tried to provide local people with a low-cost option for household water treatment. Out of 19 trained entrepreneurs, only four are currently producing filters. The goal of this evaluation was to find out what conditions lead to the successful continuation of the production and the reasons for failure. Methods: The evaluation of the potters was based on a Qualitative Comparative Analysis and the conditions looked at were: “Production”, “Collaboration”, “Market” and “Potter”. Results: Analysis showed that production problems and insufficient demand led to the termination of ceramic filter production and that both trouble-free production and high demand are necessary for a sustainable business.
Does Integrated Information Lack Subjectivity

summary : I investigate the status of subjectivity in Integrated Information Theory. This leads me to examine if Integrated Information Theory can answer the hard problem of con sciousness. On itself, Integrated Information Theory does not seem to constitute an answer to the hard problem, but could be combined with panpsychism to yield a more satisfying theory of consciousness. I will show, that even if Integrated Information Theory employs the meta physical machinery of panpsychism, Integrated Information would still suffer from a different problem, not being able to account for the subjective character of consciousness.
UNSUPERVISED FEATURE LEARNING FOR SPEECH AND MUSIC DETECTION IN RADIO BROADCASTS

Detecting speech and music is an elementary step in extracting information from radio broadcasts. Existing solutions either rely on general-purpose audio features, or build on features specifically engineered for the task. Interpreting spectrograms as images, we can apply unsupervised feature learning methods from computer vision instead. In this work, we show that features learned by a mean-covariance Restricted Boltzmann Machine partly resemble engineered features, but outperform three hand-crafted feature sets in speech and music detection on a large corpus of radio recordings. Our results demonstrate that unsupervised learning is a powerful alternative to knowledge engineering.
On the Design of Minimum BER Linear Space-Time Block Codes for MIMO Systems Equipped With MMSE Receivers

In this paper, we consider the design of a full-rate linear space-time block code for coherent multiple-input multiple-output (MIMO) communication systems under a quasi-static Rayleigh flat-fading environment. Our design targets specifically at the use of a linear minimum mean-square error (MMSE) receiver that minimizes the asymptotic average bit error rate (BER) when the transmitted signal is selected from a 4-QAM constellation. This optimization problem is solved in two main stages: 1) a lower bound on the BER is first minimized, and 2)how this minimized lower bound can be achieved is then shown. By exploiting a rigorous convex optimization technique without any assumption on the code, we prove that individual unitary and trace-orthogonal structures are the necessary and sufficient conditions to assure the minimum asymptotic average BER with an MMSE detector. An algorithm is provided for an efficient generation of our codes, and simulation results confirm that our optimally designed codes are indeed superior in performance compared to some other commonly used codes
Decellularization of porcine skeletal muscle extracellular matrix for the formulation of a matrix hydrogel: a preliminary study

Extracellular matrix (ECM) hydrogels are used as scaffolds to facilitate the repair and reconstruction of tissues. This study aimed to optimize the decellularization process of porcine skeletal muscle ECM and to formulate a matrix hydrogel scaffold. Five multi‐step methods (methods A–E) were used to generate acellular ECM from porcine skeletal muscle [rinsing in SDS, trypsin, ethylenediaminetetraacetic acid (EDTA), Triton X‐100 and/or sodium deoxycholate at 4–37°C]. The resulting ECM was evaluated using haematoxylin and eosin, 4‐6‐diamidino‐2‐phenylindole (DAPI) staining, and DNA quantification. Acellular matrix was dissolved in pepsin and gelled at 37°C. Hydrogel response to temperature was observed in vivo and in vitro. ECM components were assessed by Masson, Sirius red, and alcian blue staining, and total protein content. Acellular porcine skeletal muscle exhibited a uniform translucent white appearance. No intact nuclear residue was detected by haematoxylin and eosin staining, while DAPI staining showed a few nuclei in the matrixes produced by methods B, C, and D. Method A generated a gel that was too thin for gelation. However, the matrix obtained by rinsing in 0.2% trypsin/0.1% EDTA, 0.5% Triton X‐100, and 1% Triton X‐100/0.2% sodium deoxycholate was nuclei‐free and produced a viscous solution that formed a structurally stable white jelly‐like hydrogel. The residual DNA content of this solution was 49.37 ± 0.72 ng/mg, significantly less than in fresh skeletal muscle, and decreased to 19.22 ± 0.85 ng/mg after gelation (P < 0.05). The acellular matrix was rich in collagen and glycosaminoglycan, with a total protein concentration of 64.8 ± 6.9%. An acellular ECM hydrogel from porcine skeletal muscle was efficiently produced.
Mechanical characterization of solution-derived nanoparticle silver ink thin films

Mechanical properties of sintered silver nanoparticles are investigated via substrate curvature and nanoindentation methods. Substrate curvature measurements reveal that permanent microstructural changes occur during initial heating while subsequent annealing results in nearly elastic behavior of the thinner films. Thicker films were found to crack upon thermal treatment. The coefficient of thermal expansion was determined from linear slopes of curvature curves to be 1.9±0.097 ppm/°C, with elastic modulus and hardness determined via nanoindentation. Accounting for substrate effects, nanoindentation hardness and modulus remained constant for different film thicknesses and did not appear to be a function of annealing conditions. Hardness of 0.91 GPa and modulus of 110 GPa are somewhat lower than expected for a continuous nanocrystalline silver film, most likely due to porosity.
Challenges of studying and processing dialects in social media

Dialect features typically do not make it into formal writing, but flourish in social media. This enables largescale variational studies. We focus on three phonological features of African American Vernacular English and their manifestation as spelling variations on Twitter. We discuss to what extent our data can be used to falsify eight sociolinguistic hypotheses. To go beyond the spelling level, we require automatic analysis such as POS tagging, but social media language still challenges language technologies. We show how both newswire- and Twitter-adapted stateof-the-art POS taggers perform significantly worse on AAVE tweets, suggesting that large-scale dialect studies of language variation beyond the surface level are not feasible with out-ofthe-box NLP tools.
Reducing statistics anxiety using limited teaching resources

PurposeStudents in the marketing discipline have been reported to struggle with quantitative methods. This paper aims to focus on whether it is possible to increase student confidence and reduce anxiety with quantitative data analysis even when limited teaching resources are available. It reports on two half-day initiatives to teach quantitative methods that followed the principles of integration of method into a substantive course (as opposed to stand-alone course) and hands-on approach (as opposed to using a theoretical and hands-off approach). Design/methodology/approachOver the course of three semesters, 92 students that took part of the sessions answered a survey where they reported their basic understanding, confidence, practical abilities and anxiety with quantitative methods.FindingsThe results indicate significant improvements in self-reported basic understanding, confidence, practical abilities and anxiety. Further analysis indicated that neither gender nor previous statistical background had an impact on perceived benefit with the initiative.Practical implicationsIn all, the study indicates that integration and hands-on approaches may be beneficial to reduce anxiety and increase confidence with quantitative data analysis, even when this initiative is limited in time and resources.Originality/valueThe study presents an approach to reducing anxiety and increasing confidence with quantitative data analysis. Teaching initiatives like this may be beneficial in situations when students experience high levels of statistics anxiety.
Limited channel feedback for RF lens antenna based massive MIMO systems

In this paper, we propose a radio frequency (RF) lens-embedded massive multiple-input multiple-output (MIMO) system. To analyze the characteristics of RF lens antennas, we first introduce the beam propagation method (BPM) and use it to construct a new channel model. We next design a low complexity codebook reflecting the characteristics of the RF lens antennas for limited feedback. Numerical results confirm that, compared to conventional approaches such as random vector quantization (RVQ), the proposed system shows significant performance enhancements in terms of the achievable rate and computational complexity.
Monetary Policy and Shifts in Long Run Productivity Growth ∗

The productivity slowdown in the 1970s and the speedup in the late 1990s presented difficult challenges to monetary policymakers. The productivity slowdown has been blamed for the 1970s stagflation episode—contemporaneous stagnant growth, high unemployment, and high inflation—while the productivity acceleration has similarly been credited with powering the disinflationary boom of the late 1990s. In both cases, monetary policy is believed to have been important in determining the economy’s response to the shift in long-run growth. Although there has been a great deal of study documenting these events, there has been surprisingly little formal analysis of the appropriate monetary policy response to shifts in the growth rate of productivity. Intuitively, it is clear that policy should somehow “accommodate” supply shocks such as these, but the question is, what does that imply for the setting of interest rates? In particular, should real interest rates—which will eventually move in the same direction as the change in the rate of productivity growth—rise or fall in response to technology shocks and how much does monetary policy matter for the evolution of real and nominal variables? A further challenge for monetary policy makers arises from the difficulty in identifying in real time shifts in the growth rate of productivity. In this paper, we examine the effects of (and appropriate policy response to) shifts in the growth rate of long-run multifactor productivity (MFP), where in doing so we recognize the important practical consideration that the underlying growth rate in MFP growth is unobservable in real time and must therefore be inferred from available data. We conduct our monetary policy analysis using the two-sector DGE model developed and estimated in Edge, Laubach, and Williams (2003), and modified here to allow for persistent changes in trend productivity growth. The model incorporates habit formation in consumption, investment adjustment costs, variable capacity utilization, sticky wages and prices, and imperfect information regarding the permanence of shocks to productivity growth. We find that shifts in the long-run productivity growth rate have sizable and highly persistent effects on the real economy and inflation. In addition, these responses, particularly those of employment and inflation, are sensitive to the specification of monetary policy. This latter result contrasts with that found using stylized New Keynesian models, in which the response to growth rate shocks is relatively insensitive to the particular specification of policy.
Random walk on random walks

In this paper we study a random walk in a one-dimensional dynamic random environment consisting of a collection of independent particles performing simple symmetric random walks in a Poisson equilibrium with density 2 (0;1). At each step the random walk performs a nearest-neighbour jump, moving to the right with probability p when it is on a vacant site and probability p when it is on an occupied site. Assuming that p 2 (0; 1) and p 6= 1 , we show that the position of the random walk satises a strong law of large numbers, a functional central limit theorem and a large deviation bound, provided is large enough. The proof is based on the construction of a renewal structure together with a multiscale renormalisation argument.
Effect of furosemide on hyperpnea-induced airway obstruction, injury, and microvascular leakage.

Furosemide attenuates hyperpnea-induced airway obstruction (HIAO) in asthmatic subjects via unknown mechanism(s). We studied the effect of furosemide on dry air-induced bronchoconstriction, mucosal injury, and bronchovascular hyperpermeability in a canine model of exercise-induced asthma. Peripheral airway resistance (Rp) was recorded before and after a 2-min dry-air challenge (DAC) at 2,000 ml/min. After pretreatment with aerosolized saline containing 0.75% dimethyl sulfoxide, DAC increased Rp 72 +/- 11% (SE, n = 7) above baseline; aerosolized furosemide (10(-3) M) reduced this response by approximately 50 +/- 6% (P < 0.01). To assess bronchovascular permeability, colloidal carbon was injected (1 ml/kg i.v.) 1 min before DAC, and after 1 h, the vehicle- and furosemide-treated airways were prepared for morphometric analysis. Light microscopy confirmed previous studies showing that DAC damaged the airway epithelium and enhanced bronchovascular permeability. Furosemide did not inhibit dry air-induced mucosal injury or bronchovascular hyperpermeability and in fact tended to increase airway damage and vascular leakage. This positive trend toward enhanced bronchovascular permeability in DAC canine peripheral airways is consistent with the hypothesis that furosemide inhibits HIAO in part by enhancing microvascular leakage and thus counterbalancing the evaporative water loss that occurs during hyperpnea.
Type 1 Diabetes in the BB Rat: A Polygenic Disease

OBJECTIVE Two type 1 diabetes susceptibility genes have been identified in the spontaneously diabetic biobreeding diabetes-prone (BBDP) rat, the major histocompatibility complex (MHC) (RT1) class II u haplotype (Iddm1) and Gimap5 (Iddm2). The strong effects of these have impeded previous efforts to map additional loci. We tested the hypothesis that type 1 diabetes is a polygenic disease in the BBDP rat. RESEARCH DESIGN AND METHODS We performed the most comprehensive genome-wide linkage analysis for type 1 diabetes, age of disease onset (AOO), and insulitis subphenotypes in 574 F2 animals from a cross-intercross between BBDP and type 1 diabetes–resistant, double congenic ACI.BBDP-RT1u,Gimap5 (ACI.BB1u.lyp) rats, where both Iddm1 and Iddm2 were fixed as BBDP. RESULTS A total of 19% of these F2 animals developed type 1 diabetes, and eight type 1 diabetes susceptibility loci were mapped, six showing significant linkage (chromosomes 1, 3, 6 [two loci], 12, and 14) and two (chromosomes 2 and 17) suggestive linkage. The chromosomes 6, 12, and 14 intervals were also linked to the severity of islet infiltration by immunocytes, while those on chromosomes 1, 6 (two loci), 14, 17, and a type 1 diabetes–unlinked chromosome 8 interval showed significant linkage to the degree of islet atrophy. Four loci exhibited suggestive linkage to AOO on chromosomes 2 (two loci), 7, and 18 but were unlinked to type 1 diabetes. INS, PTPN22, IL2/IL21, C1QTNF6, and C12orf30, associated with human type 1 diabetes, are contained within the chromosomes 1, 2, 7, and 12 loci. CONCLUSIONS This study demonstrates that the BBDP diabetic syndrome is a complex, polygenic disease that may share additional susceptibility genes besides MHC class II with human type 1 diabetes.
A Predictive Model for Financial Literacy among the Educated Youth in Kerala, India

ABSTRACT The economic importance of financial literacy among individuals necessitates policy intervention. Estimation of financial literacy is a prerequisite for strategies to improve financial literacy. This paper, using data collected from the educated young adults in Kerala, the most literate state in India, builds a predictive model for financial literacy employing logistic regression. The study reveals the low level of financial literacy in the state. The model points to the significance of gender, age, religion, discipline of study, occupation, and personal income as determinants of financial literacy. The findings have implications for policies aimed at improving the financial literacy of young adults in India.
Article in Press G Model Journal of Neuroscience Methods Development and Validation of Consensus Clustering-based Framework for Brain Segmentation Using Resting Fmri

• Develop and validate consensus clustering framework for segmenting brain regions. • Develop and validate criteria to determine optimal number of clusters. • Performance evaluated using extensive computer simulations and resting-state fMRI. • Methods optimal for group-level segmentation clarified. a b s t r a c t Background: Clustering methods are increasingly employed to segment brain regions into functional subdivisions using resting-state functional magnetic resonance imaging (rs-fMRI). However, these methods are highly sensitive to the (i) precise algorithms employed, (ii) their initializations, and (iii) metrics used for uncovering the optimal number of clusters from the data. New method: To address these issues, we develop a novel consensus clustering evidence accumulation (CC-EAC) framework, which effectively combines multiple clustering methods for segmenting brain regions using rs-fMRI data. Using extensive computer simulations, we examine the performance of widely used clustering algorithms including K-means, hierarchical, and spectral clustering as well as their combinations. We also examine the accuracy and validity of five objective criteria for determining the optimal number of clusters: mutual information, variation of information, modified silhouette, Rand index, and probabilistic Rand index. Results: A CC-EAC framework with a combination of base K-means clustering (KC) and hierarchical clustering (HC) with probabilistic Rand index as the criterion for choosing the optimal number of clusters, accurately uncovered the correct number of clusters from simulated datasets. In experimental rs-fMRI data, these methods reliably detected functional subdivisions of the supplementary motor area, insula, intraparietal sulcus, angular gyrus, and striatum. Comparison with existing methods: Unlike conventional approaches, CC-EAC can accurately determine the optimal number of stable clusters in rs-fMRI data, and is robust to initialization and choice of free parameters. Conclusions: A novel CC-EAC framework is proposed for segmenting brain regions, by effectively combining multiple clustering methods and identifying optimal stable functional clusters in rs-fMRI data.
A Regulatory Role for TRAF1 in Antigen-induced Apoptosis of  T Cells

Tumor necrosis factor receptor (TNFR)–associated factor 2 (TRAF2) and TRAF1 were found as components of the TNFR2 signaling complex, which exerts multiple biological effects on cells such as cell proliferation, cytokine production, and cell death. In the TNFR2-mediated signaling pathways, TRAF2 works as a mediator for activation signals such as NF-κB, but the role of TRAF1 has not been previously determined. Here we show in transgenic mice that TRAF1 overexpression inhibits antigen-induced apoptosis of CD8+ T lymphocytes. Our results demonstrate a biological role for TRAF1 as a regulator of apoptotic signals and also support the hypothesis that the combination of TRAF proteins in a given cell type determines distinct biological effects triggered by members of the TNF receptor superfamily.