Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing with Politics for Money and Power in Infrastructure

Policy recommendations for infrastructure provision usually build on a well-established understanding of best practice for sector governance. Too rarely are they adapted to the country-specific political environment even if this is an area where policy choices are likely to be subject to private agendas in politics. The fact that such private agendas are often ignored goes a long way toward explaining why infrastructure policies fail and why best practice can be counterproductive. While non-benevolence and rent-seeking are well described in the literature and anecdotes abound, there is only limited consideration of how the different incentive problems in politics impede policy improvements in infrastructure. This paper addresses why politics in infrastructure cannot be ignored, drawing on theoretical results and a systematic review of experiences. It reviews how different private agendas in politics will have different impacts for sector-governance decisions -- and hence service delivery. The concept of best practice in policy recommendations should be reconsidered in a wide perspective and allow for tailored solutions based on an understanding of the given incentive problems. Policy recommendations should take into account how coordination trade-offs may complicate efforts to reduce the possible impact of private agendas on infrastructure policy decisions. Although more transparency linked to service delivery indicators is a"safe"recommendation, it is also clear that the demand for good governance will not be sufficient to secure political accountability in a sector with huge vested interests combined with complicated funding schemes and complex contracts.
Blinking on the Bench: How Judges Decide Cases

How do judges judge? Do they apply law to facts in a mechanical and deliberative way, as the formalists suggest they do, or do they rely on hunches and gut feelings, as the realists maintain? Debate has raged for decades, but researchers have offered little hard evidence in support of either model. Relying on empirical studies of judicial reasoning and decision making, we propose an entirely new model of judging that provides a more accurate explanation of judicial behavior. Our model accounts for the tendency of the human brain to make automatic, snap judgments, which are surprisingly accurate, but which can also lead to erroneous decisions. Equipped with a better understanding of judging, we then propose several reforms that should lead to more just and accurate outcomes.
The light-deficient climates of western Central African evergreen forests

Rainfall thresholds under which forests grow in Central Africa are lower than those of Amazonia and southeast Asia. Attention is thus regularly paid to rainfall whose seasonality and interannual variability has been shown to control Central African forests’ water balance and photosynthetic activity. Nonetheless, light availability is also recognized as a key factor to tropical forests. Therefore this study aims to explore the light conditions prevailing across Central Africa, and their potential impact on forests’ traits. Using satellite estimates of hourly irradiance, we find first that the four main types of diurnal cycles of irradiance extracted translate into different levels of rainfall, evapotranspiration, direct and diffuse light. Then accounting for scale interactions between the diurnal and annual cycles, we show that the daily quantity and quality of light considerably vary across Central African forests during the annual cycle: the uniqueness of western Central Africa and Gabon in particular, with strongly light-deficient climates especially during the main dry season, points out. Lastly, using an original map of terra firme forests, we also show that most of the evergreen forests are located in western Central Africa and Gabon. We postulate that despite mean annual precipitation below 2000 mm yr−1, the light-deficient climates of western Central Africa can harbour evergreen forests because of an extensive low-level cloudiness developing during the June–September main dry season, which strongly reduces the water demand and enhances the quality of light available for tree photosynthesis. These findings pave the way for further analyses of the past and future changes in the light-deficient climates of western Central Africa and the vulnerability of evergreen forests to these changes.
Speech enhancement by combination of transient emphasis and noise cancelation

This paper evaluates the effectiveness of combining speech modification techniques that enhance transition components with active noise cancellation to improve the intelligibility of speech in noise. Two speech modification techniques were considered. One is based on wavelet-packet analysis, and the second uses a fixed filter, derived from time-frequency analysis, that emphasizes high frequencies. Active noise cancellation was provided by Bose noise-cancelling headphones. The test noise was real, generated by a ground auxiliary generator on the tarmac at an Air National Guard facility. The test signals were speech tokens from the modified rhyme (psycho-acoustic) test, recorded by a male speaker. This paradigm was used to measure word recognition rates at various signal-to-noise ratios. Active noise cancellation by itself provided over 40% increase in word recognition, while the modified speech and fixed filter techniques alone provided up to 20% improvement, depending on the signal-to-noise ratio. In combination, the speech modification approaches provided over 15% additional improvement in intelligibility over noise cancellation alone.
Scalable and Probabilistic Leaderless BFT Consensus through Metastability

This paper introduces a family of leaderless Byzantine fault tolerance protocols, built around a metastable mechanism via network subsampling. These protocols provide a strong probabilistic safety guarantee in the presence of Byzantine adversaries while their concurrent and leaderless nature enables them to achieve high throughput and scalability. Unlike blockchains that rely on proof-of-work, they are quiescent and green. Unlike traditional consensus protocols where one or more nodes typically process linear bits in the number of total nodes per decision, no node processes more than logarithmic bits. It does not require accurate knowledge of all participants and exposes new possible tradeoffs and improvements in safety and liveness for building consensus protocols. The paper describes the Snow protocol family, analyzes its guarantees, and describes how it can be used to construct the core of an internet-scale electronic payment system called Avalanche, which is evaluated in a large scale deployment. Experiments demonstrate that the system can achieve high throughput (3400 tps), provide low confirmation latency (1.35 sec), and scale well compared to existing systems that deliver similar functionality. For our implementation and setup, the bottleneck of the system is in transaction verification.
Pictorial Personality Traits Questionnaire for Children (PPTQ-C)—A New Measure of Children's Personality Traits

In order to adjust personality measurements to children's developmental level, we constructed the Pictorial Personality Traits Questionnaire for Children (PPTQ-C). To validate the measure, we conducted a study with a total group of 1028 children aged between 7 and 13 years old. Structural validity was established through Exploratory Structural Equation Model (ESEM). Criterion validity was confirmed with a multitrait-multimethod analysis for which we introduced the children's self-assessment scores from the Big Five Questionnaire for Children. Despite some problems with reliability, one can conclude that the PPTQ-C can be a valid instrument for measuring personality traits, particularly in a group of young children (aged ~7–10 years).
Integrating high yielding crops into a Taranaki dairying system

cropping sequences were introduced to a pasture-based dairy system with the aim of improving the annual feed supply, herd productivity and overall profitability. two farmlets were established on the Waimate West demonstration Farm (taranaki) in June 2007 and ran for 5 years. the All-grass farmlet was a pasture-only system (except for 70 kg/cow palm kernel expeller in one year) and the cropping farmlet had on average 12.5% of the farm cropped each year plus palm kernel expeller (250 kg/cow/year over 3 years). crop sequences varied in duration from 12 to 28 months. crops grown were maize (for silage), turnips, chicory, rape, oats, barley and triticale. stocking rates were 4.0 and 4.2 cows/ha for the All-grass and cropping farmlets, respectively. Pasture growth for the two farmlets was similar, averaging 16.6 t dM/ha/year. the inclusion of crops added an extra 1.7 t dM/ha/year over the Allgrass treatment, averaged over the 5-year trial. in the first 2 years, milksolids (MS) production per hectare was 2% lower for the cropping farmlet (1145 kg Ms/ ha) than for the All-grass farmlet (1165 kg Ms/ha), but was 11% higher (1237 vs. 1112 kg Ms/ha) over the next 2 years, increasing to a 27% advantage (1453 vs. 1143 kg MS/ha) in the fifth year. Financial analysis indicated a $338 lower operating profit for the Cropping farmlet for the first 2 years but there was an advantage of $560/ ha/annum over the next 3 years. introducing cropping onto a dairy farm system can increase Ms production and profit. Careful consideration must be given to the choice of crops to maximise dM yield and minimise the cost of production. cropping on dairy farms can be successfully implemented, but is dependent on successful crop establishment and efficient feed management. there is potential for sustained higher Ms production per cow and higher per ha by including crops in the system, but the potential may not be realised immediately due to reduced area for grazing while the first crops are being established.
Intercellular communication in malignant pleural mesothelioma: properties of tunneling nanotubes

Malignant pleural mesothelioma is a particularly aggressive and locally invasive malignancy with a poor prognosis despite advances in understanding of cancer cell biology and development of new therapies. At the cellular level, cultured mesothelioma cells present a mesenchymal appearance and a strong capacity for local cellular invasion. One important but underexplored area of mesothelioma cell biology is intercellular communication. Our group has previously characterized in multiple histological subtypes of mesothelioma a unique cellular protrusion known as tunneling nanotubes (TnTs). TnTs are long, actin filament-based, narrow cytoplasmic extensions that are non-adherent when cultured in vitro and are capable of shuttling cellular cargo between connected cells. Our prior work confirmed the presence of nanotube structures in tumors resected from patients with human mesothelioma. In our current study, we quantified the number of TnTs/cell among various mesothelioma subtypes and normal mesothelial cells using confocal microscopic techniques. We also examined changes in TnT length over time in comparison to cell proliferation. We further examined potential approaches to the in vivo study of TnTs in animal models of cancer. We have developed novel approaches to study TnTs in aggressive solid tumor malignancies and define fundamental characteristics of TnTs in malignant mesothelioma. There is mounting evidence that TnTs play an important role in intercellular communication in mesothelioma and thus merit further investigation of their role in vivo.
Distribution-dependent and Time-uniform Bounds for Piecewise i.i.d Bandits

We consider the setup of stochastic multi-armed bandits in the case when reward distributions are piecewise i.i. d. and bounded with unknown changepoints. We focus on the case when changes happen simultaneously on all arms, and in stark contrast with the existing literature, we target gap-dependent (as opposed to only gap-independent) regret bounds involving the magnitude of changes $(\Delta^{chg}_{i,g})$ and optimality-gaps ($\Delta^{opt}_{i,g}$). Diverging from previous works, we assume the more realistic scenario that there can be undetectable changepoint gaps and under a different set of assumptions, we show that as long as the compounded delayed detection for each changepoint is bounded there is no need for forced exploration to actively detect changepoints. We introduce two adaptations of UCB-strategies that employ scan-statistics in order to actively detect the changepoints, without knowing in advance the changepoints and also the mean before and after any change. Our first method \UCBLCPD does not know the number of changepoints $G$ or time horizon $T$ and achieves the first time-uniform concentration bound for this setting using the Laplace method of integration. The second strategy \ImpCPD makes use of the knowledge of $T$ to achieve the order optimal regret bound of $\min\big\lbrace O(\sum\limits_{i=1}^{K} \sum\limits_{g=1}^{G}\frac{\log(T/H_{1,g})}{\Delta^{opt}_{i,g}}), O(\sqrt{GT})\big\rbrace$, (where $H_{1,g}$ is the problem complexity) thereby closing an important gap with respect to the lower bound in a specific challenging setting. Our theoretical findings are supported by numerical experiments on synthetic and real-life datasets.
HOW DOES SELF-CONTROL OPERATE? A FOCUS ON IMPULSE BUYING

behavior. This research aims to shed light on the importance of impulse buying study, like any other spheres of human life, as an outcome of self-control process. This paper considers different types of self-control failure resulting from conflicting standards, the degree to which people monitor their behavior, and the depletion of self-regulatory resources. This is followed by explaining the current self-control approaches in impulse buying studies. In addition, integrating different self-control models, the present paper provides a general framework of self-control process with a focus on impulse buying. The framework integrates the components of impulses, conflict, resistance, and self-control outcome that should be considered jointly when analyzing self-control phenomena.
Single-sided adaptive estimation of multi-path millimeter wave channels

Millimeter wave (mmWave) cellular systems will enable ultra high data rates by communicating over the large bandwidth available in mmWave frequencies. To overcome the channel propagation characteristics in this frequency band, large antenna arrays need to be deployed at both the base station and mobile users. While these large arrays provide sufficient beamforming gains to meet the required link margins, they make it challenging to estimate the mmWave channel. In this paper, we propose a mmWave channel estimation algorithm that exploits the sparse nature of the channel and leverages tools from adaptive compressed sensing to efficiently estimate the channel with a small training overhead. The proposed algorithm considers practical hardware constraints on the training beamforming design, and does not require the availability of a feedback channel between the base station and the mobile user. Simulation results indicate that comparable precoding gains can be achieved by the proposed channel estimation algorithm relative to the case when perfect channel knowledge exists.
Inference of Haplotypes from Samples of Diploid Populations: Complexity and Algorithms

The next phase of human genomics will involve large-scale screens of populations for significant DNA polymorphisms, notably single nucleotide polymorphisms (SNPs). Dense human SNP maps are currently under construction. However, the utility of those maps and screens will be limited by the fact that humans are diploid and it is presently difficult to get separate data on the two "copies. " Hence, genotype (blended) SNP data will be collected, and the desired haplotype (partitioned) data must then be (partially) inferred. A particular nondeterministic inference algorithm was proposed and studied by Clark (1990) and extensively used by Clark et al. (1998). In this paper, we more closely examine that inference method and the question of whether we can obtain an efficient, deterministic variant to optimize the obtained inferences. We show that the problem is NP-hard and, in fact, Max-SNP complete; that the reduction creates problem instances conforming to a severe restriction believed to hold in real data (Clark, 1990); and that even if we first use a natural exponential-time operation, the remaining optimization problem is NP-hard. However, we also develop, implement, and test an approach based on that operation and (integer) linear programming. The approach works quickly and correctly on simulated data.
A large-scale data collection scheme for distributed Topic-Based Pub/Sub

In this paper, we propose a scalable data collection scheme for distributed Topic-Based Pub/Sub (TBPS) messaging that can prevent overloads in network processes in the large-scale IoT applications. Our proposal scheme employs “Collective Store and Forwarding,” which stores and merges multiple small size messages into one large message along a multi-hop tree structure on the structured overlay for TBPS, taking into account the delivery time constraints. This makes it possible to reduce the overhead of network process even when a large number of sensor data is published asynchronously. We also propose a tree construction method for adjusting maximum network process load on nodes called the “Adaptive Data Collection Tree. ” Simulation results show that compared to existing schemes, our proposal schemes can reduce a network occupation time by 90% to collect data from 10,000 publishers.
Clustering Categorical Data Based on Representatives

Clustering of categorical data is one of the data mining techniques, which helps in identifying clusters within the domain space. In this paper we present a new method to cluster categorical data. This new representative based method works in three phases. The dissimilarity matrix, neighbor matrix and the initial clusters are formed in first phase. Merging of clusters is performed in the second phase by relocating the objects using the neighborhood concept. In the third phase, mode of attributes of clusters is computed, and phase I and Phase II are applied for the tuples formed from these representatives. The proposed method is experimented with the well known data sets from UCI data repository, soybean, zoo and mushroom data set.
How software architects collaborate: Insights from collaborative software design in practice

The increasingly complex software systems are developed by globally distributed engineering teams consisting of a number of members who collaborate to gather the requirements, as well as design, implement, and test the system. Unlike other development activities, collaborative software design has not yet been studied extensively, and thus it is not fully understood how it is conducted in practice. We have commenced a series of studies to address this. As the first step, we have interviewed architects at a global software solutions provider to observe how collaborative software design works in practice. In this paper, we report the observations and insights we gained from the interviews related to (1) the various roles of software architects in collaborative software design, (2) the project-specific networks of software architects, (3) the impacts of geographic distribution, and (4) the collaboration cost drivers. We also discuss how we are using these insights to shape up our subsequent research.
Diagonal parameter shifts due to nearest-neighbor displacements in empirical tight-binding theory

Nanoscale heterostructures are generally characterized by local strain variations. Because the atoms in such systems can be irregularly positioned, theroretical models and parameterizations that are restricted to hydrostatic and uniaxial strain are generally not applicable. To address this shortcoming, a method that enables the incorporation of general distortions into the empirical tight binding model is presented. The method shifts the diagonal Hamiltonian matrix elements due to displacements of neighboring atoms from their ideal bulk positions. The new, efficient, and flexible method is developed for zincblende semiconductors and employed to calculate gaps for GaAs and InAs under hydrostatic and uniaxial strain. Where experimental and theoretical data are available our new method compares favorably with other methods, yet it is not restricted to the cases of uniaxial or hydrostatic strain. Because our method handles arbitrary nearest-neighbor displacements it permits the incorporation of diagonal parameter shifts in general, three-dimensional nanoscale electronic structure simulations, such as the nanoelectronic modeling tool ~NEMO 3D!
AD Award Number : DAMD 1799-1-9034 TITLE : Ultrasound Imaging Initiative

A real-time 3-D imaging system requires the development of a beamformer that can generate many beams simultaneously. In this paper, we discuss and evaluate a suitable synthetic aperture beamformer. The proposed beamformer is based on a pipelined network of high speed digital signal processors (DSP). By using simple interpolation-based beamforming, only a few calculations per pixel are required for each channel, and an entire 2-D synthetic aperture image can be formed in the time of one transmit event. The performance of this beamformer was explored using a computer simulation of the radiation pattern. The simulations were done for a full 64-element array and a sparse array with the same receive aperture but only five transmit elements. We assessed the effects of changing the sampling rate and amplitude quantization by comparing the relative levels of secondary lobes in the radiation patterns. The results show that the proposed beamformer produces a radiation pattern equivalent to a conventional beamformer using baseband demodulation, provided that the sampling rate is approximately 10 times the center frequency of the transducer (34% bandwidth pulse). The simulations also show that the sparse array is not significantly more sensitive to delay or amplitude quantization than the full array.
Towards Build-Time Interoperability of Workflow Definition Languages

As the number and complexity of workflow definition languages grows, ensuring interoperability between them becomes more difficult, with most effort being concentrated on achieving run-time interoperability. The contribution of this paper is to argue for an alternative approach-with interoperation being achieved during build-time, through the use of what we term an intermediate workflow representation (IWR) format, with this format acting as a mediator to carry out language-to-language conversions. In this paper we identify the requirements of such an approach, with the main benefit being that legacy workflows, defined in different workflow definition languages, might be used in conjunction-and in a fashion that is seamless to the user.
DE NOVO METHOD OF DEVELOPING SILK FIBROIN HYDROGEL AIM FOR USING AS A DERMAL SCAFFOLD BY GAMMA IRRADIATION

Tissue engineering of skin is a rapidly developing field in biomedical engineering research. One of the challenges in skin tissue engineering (STE) is molding engineered skin tissue to create a dermal scaffold that could be used in wound care or skin grafting. We developed a novel method for cross-linking a silk fibroin solution by gamma irradiation to form a hydrogel that might serve as a dermal scaffold. The silk fibroin hydrogel was not cytotoxic to human fibroblasts or human keratinocytes, which are analyzed by cytotoxicity and direct contact tests. The mechanical properties of the silk fibroin hydrogel formed by gamma irradiation method were improved mechanical properties to those of a silk fibroin hydrogen created using a freeze-drying method. The silk fibroin hydrogel created using this novel method has potential use as a dermal scaffold in STE.