Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Effect of Leaders on Public Sector Productivity : The Case of School Principals

Although much has been written about the importance of leadership in the determination of organizational success, there is little quantitative evidence due to the difficulty of separating the impact of leaders from other organizational components – particularly in the public sector. Schools provide an especially rich environment for studying the impact of public sector management, not only because of the hypothesized importance of leadership but also because of the plentiful achievement data that provide information on institutional outcomes. Outcomebased estimates of principal value-added to student achievement reveal significant variation in principal quality that appears to be larger for high-poverty schools. Alternate lower-bound estimates based on direct estimation of the variance yield smaller estimates of the variation in principal productivity but ones that are still important, particularly for high poverty schools. Patterns of teacher exits by principal quality validate the notion that a primary channel for principal influence is the management of the teacher force. Finally, looking at principal transitions by quality reveals little systematic evidence that more effective leaders have a higher probability of exiting high poverty schools.
From rheometry to rheology

Using a variety of examples from the recent literature on extensional flow of polymer solutions, this paper shows that simple constitutive equations are unable to capture the diversity of chain conformations in such flows. Such diversity is a feature of extensional flows and arises because deformation leads to significant chain extension. Substantial local extension appears even at low strains and the behaviour of these stretched out portions influences the dynamics of the chain and makes a dominant contribution to the stress. Both the distribution function and the chain conformation appear to follow different paths during stretching and relaxation. As a result the second moment of the distribution function does not contain enough information to correctly predict the dynamics. Resolution of this deficiency in simple constitutive models is one of the challenges for rheology.
Public Auditing with Privacy Protection in a Multi-User Model of Cloud-Assisted Body Sensor Networks

Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users’ medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs’ applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs’ deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models.
Improved robust current shaping control for shunt active filters

This paper presents some improvements over the previously presented current-shaping control for parallel active filters. The proposed strategy allows the active filter to operate with a reduced number of sensors, and dependently of phase synchronization schemes for references generation. A new realization proposal employs a quasi-resonant system frequency adaptable to implement complex impedances, and have low interaction with harmonic components in the grid. An additional quasi-resonant scheme in a stationary reference frame is proposed to extend the current shaping control in order to achieve great mitigation capability. The energy flow control in this paper deals with further uncertainties, which results in an enhanced robust design methodology. Experimental results are presented using a 1kVA prototype.
DyPO

Modern multiprocessor systems-on-chip (MpSoCs) offer tremendous power and performance optimization opportunities by tuning thousands of potential voltage, frequency and core configurations. As the workload phases change at runtime, different configurations may become optimal with respect to power, performance or other metrics. Identifying the optimal configuration at runtime is infeasible due to the large number of workloads and configurations. This paper proposes a novel methodology that can find the Pareto-optimal configurations at runtime as a function of the workload. To achieve this, we perform an extensive offline characterization to find classifiers that map performance counters to optimal configurations. Then, we use these classifiers and performance counters at runtime to choose Pareto-optimal configurations. We evaluate the proposed methodology by maximizing the performance per watt for 18 single- and multi-threaded applications. Our experiments demonstrate an average increase of 93%, 81% and 6% in performance per watt compared to the interactive, ondemand and powersave governors, respectively.
Matching Control Flow of Program Versions

In many application areas, including piracy detection, software debugging and maintenance, situations arise in which there is a need for comparing two versions of a program that dynamically behave the same even though they statically appear to be different. Recently dynamic matching [18] was proposed by us which uses execution histories to automatically produce mappings between instructions in the two program versions. The mappings then can be used to understand the correspondence between the two versions by a user involved in software piracy detection or a comparison checker involved in debugging of optimized code. However, if a program's control flow is substantially altered, which usually occurs in obfuscation or even manual transformations, mappings at instruction level are not sufficient to enable a good understanding of the correspondence. In this paper, we present a comprehensive dynamic matching algorithm with the focus on call graph and control flow matching. Our technique works in the presence of aggressive control flow transformations (both interprocedural such as function Mining/outlining and intraprocedural such as control flow flattening) and produces mappings of interprocedural and intraprocedural control flow in addition to mapping between instructions. We evaluated our dynamic matching algorithms by attempting to match original program with versions that were subjected to popular obfuscation and control flow altering transformations. Our experimental results show that the control flow mappings produced are highly accurate and complete, for the programs considered.
A Comparison of Closed-Loop Performance of Multirotor Configurations Using Non-Linear Dynamic Inversion Control

Multirotor is the umbrella term for the family of unmanned aircraft, which include the quadrotor, hexarotor and other vertical take-off and landing (VTOL) aircraft that employ multiple main rotors for lift and control. Development and testing of novel multirotor designs has been aided by the proliferation of 3D printing and inexpensive flight controllers and components. Different multirotor configurations exhibit specific strengths, while presenting unique challenges with regards to design and control. This article highlights the primary differences between three multirotor platforms: a quadrotor; a fully-actuated hexarotor; and an octorotor. Each platform is modelled and then controlled using non-linear dynamic inversion. The differences in dynamics, control and performance are then discussed.
TIGER: Querying large tables through criteria extension

Sales on the Internet have increased significantly during the last decade, and so, it is crucial for companies to retain customers on their web site. Among all strategies towards this goal, providing customers with a flexible search tool is a crucial issue. In this paper, we propose an approach, called TIGER, for handling such flexibility automatically. More precisely, if the search criteria of a given query to a relational table or a Web catalog are too restrictive, our approach computes a new query combining extensions of the criteria. This new query maximizes the quality of the answer, while being as close as possible to the original query. Experiments show that our approach improves the quality of queries, in the sense explained just above.
C-Type Lectin Receptor (CLR)–Fc Fusion Proteins As Tools to Screen for Novel CLR/Bacteria Interactions: An Exemplary Study on Preselected Campylobacter jejuni Isolates

C-type lectin receptors (CLRs) are carbohydrate-binding receptors that recognize their ligands often in a Ca2+-dependent manner. Upon ligand binding, myeloid CLRs in innate immunity trigger or inhibit a variety of signaling pathways, thus initiating or modulating effector functions such as cytokine production, phagocytosis, and antigen presentation. CLRs bind to various pathogens, including viruses, fungi, parasites, and bacteria. The bacterium Campylobacter jejuni (C. jejuni) is a very frequent Gram-negative zoonotic pathogen of humans, causing severe intestinal symptoms. Interestingly, C. jejuni expresses several glycosylated surface structures, for example, the capsular polysaccharide (CPS), lipooligosaccharide (LOS), and envelope proteins. This “Methods” paper describes applications of CLR–Fc fusion proteins to screen for yet unknown CLR/bacteria interactions using C. jejuni as an example. ELISA-based detection of CLR/bacteria interactions allows a first prescreening that is further confirmed by flow cytometry-based binding analysis and visualized using confocal microscopy. By applying these methods, we identified Dectin-1 as a novel CLR recognizing two selected C. jejuni isolates with different LOS and CPS genotypes. In conclusion, the here-described applications of CLR–Fc fusion proteins represent useful methods to screen for and identify novel CLR/bacteria interactions.
Quality Assessment of Ambulatory ECG Using Wavelet Entropy of the HRV Signal

Data in recordings obtained from ambulatory patients using wearable sensors are often corrupted by motion artefact and are, in general, noisier than the data obtained from the nonmobile patients. Identifying and ignoring erroneous measurements from these data is very important, if wearable sensors are to be incorporated into clinical practice. In this paper, we propose a novel Signal Quality Index, intended to assess whether reliable heart rates can be obtained from a single channel of ECG collected from ambulatory patients, using wearable sensors. The proposed system is based on wavelet entropy measurements of the heart rate variability signal. The system was trained and tested on expert-labeled data from a particular wearable sensor and was also tested on labeled data from a different sensor. The sensitivities and specificities achieved were 94% and 98%, respectively, on data from the same sensor as the training set, and 91% and 97%, respectively, on data from a different sensor, indicating the potential of the system to generalize across different sensors. Because the system relies on a single channel of ECG, it has the potential for inclusion in applications using wearable sensors and in the most basic clinical environments.
Missing data in FFQs: making assumptions about item non-response

Abstract Objective FFQs are a popular method of capturing dietary information in epidemiological studies and may be used to derive dietary exposures such as nutrient intake or overall dietary patterns and diet quality. As FFQs can involve large numbers of questions, participants may fail to respond to all questions, leaving researchers to decide how to deal with missing data when deriving intake measures. The aim of the present commentary is to discuss the current practice for dealing with item non-response in FFQs and to propose a research agenda for reporting and handling missing data in FFQs. Results Single imputation techniques, such as zero imputation (assuming no consumption of the item) or mean imputation, are commonly used to deal with item non-response in FFQs. However, single imputation methods make strong assumptions about the missing data mechanism and do not reflect the uncertainty created by the missing data. This can lead to incorrect inference about associations between diet and health outcomes. Although the use of multiple imputation methods in epidemiology has increased, these have seldom been used in the field of nutritional epidemiology to address missing data in FFQs. We discuss methods for dealing with item non-response in FFQs, highlighting the assumptions made under each approach. Conclusions Researchers analysing FFQs should ensure that missing data are handled appropriately and clearly report how missing data were treated in analyses. Simulation studies are required to enable systematic evaluation of the utility of various methods for handling item non-response in FFQs under different assumptions about the missing data mechanism.
Phylogeny and source climate impact seed dormancy and germination of restoration-relevant forb species

For many species and seed sources used in restoration activities, specific seed germination requirements are often unknown. Because seed dormancy and germination traits can be constrained by phylogenetic history, related species are often assumed to have similar traits. However, significant variation in these traits is also present within species as a result of adaptation to local climatic conditions. A growing number of studies have attempted to disentangle how phylogeny and climate influence seed dormancy and germination traits, but they have focused primarily on species-level effects, ignoring potential population-level variation. We examined the relationships between phylogeny, climate, and seed dormancy and germination traits for 24 populations of eight native, restoration-relevant forb species found in a wide range of climatic conditions in the Southwest United States. The seeds were exposed to eight temperature and stratification length regimes designed to mimic regional climatic conditions. Phylogenetic relatedness, overall climatic conditions, and temperature conditions at the site were all significantly correlated with final germination response, with significant among-population variation in germination response across incubation treatments for seven of our eight study species. Notably, germination during stratification was significantly predicted by precipitation seasonality and differed significantly among populations for seven species. While previous studies have not examined germination during stratification as a potential trait influencing overall germination response, our results suggest that this trait should be included in germination studies as well as seed sourcing decisions. Results of this study deepen our understanding of the relationships between source climate, species identity, and germination, leading to improved seed sourcing decisions for restorations.
Probabilistic Safety Verification of Stochastic Hybrid Systems Using Barrier Certificates

The problem of probabilistic safety verification of stochastic hybrid systems is to check whether the probability that a given system will reach an unsafe region from certain initial states can be bounded by some given probability threshold. The paper considers stochastic hybrid systems where the behavior is governed by polynomial equalities and inequalities, as for usual hybrid systems, but the initial states follow some stochastic distributions. It proposes a new barrier certificate based method for probabilistic safety verification which guarantees the absolute safety in a infinite time horizon that is beyond the reach of existing techniques using either statistical model checking or probabilistic reachable set computation. It also gives a novel computational approach, by building and solving a constrained optimization problem coming from verification conditions of barrier certificates, to compute the lower bound on safety probabilities which can be compared with the given threshold. Experimental evidence is provided demonstrating the applicability of our approach on several benchmarks.
Health Professional Knowledge of Breastfeeding: Are the Health Risks of Infant Formula Feeding Accurately Conveyed by the Titles and Abstracts of Journal Articles?

Effective promotion of breastfeeding is constrained if health professionals' knowledge on its importance is deficient. This study asks whether formula feeding is named as the risk factor in published research or whether it is considered the unspoken norm. A systematic analysis is conducted of the information content of titles and abstracts of 78 studies that report poorer health among formula-fed infants. This shows a surprising silence in the studies examined; formula is rarely named in publication titles or abstracts as an exposure increasing health risk. In 30% of cases, titles imply misleadingly that breastfeeding raises health risk. Only 11% of abstracts identify formula feeding as a health risk exposure. Initiatives to increase breastfeeding have described the importance of accurate language and well-informed health professional support. If widespread, this skew in communication of research findings may reduce health professionals' knowledge and support for breastfeeding. J Hum Lact. 25(3):350-358.
SOX9 is a driver of aggressive prostate cancer by promoting invasion, cell fate and cytoskeleton alterations and epithelial to mesenchymal transition

Aggressive lethal prostate cancer is characterised by tumour invasion, metastasis and androgen resistance. Understanding the mechanisms by which localised disease progresses to advanced lethal stages is key to the development of effective therapies. Here we have identified a novel role for the transcription factor, SOX9, as a driver of aggressive invasive prostate cancer. Using genetically modified mouse models, we show that increased Sox9 expression in the prostate epithelia of animals with Pten loss leads to a highly invasive phenotype and metastasis. In depth analysis of these mice and related in vitro models reveals that SOX9 acts a key regulator of various processes that together promote tumour progression. We show that this factor promotes cell lineage plasticity with cells acquiring properties of basal stem cells and an increase in proliferation. In addition, increased SOX9 leads to changes in cytoskeleton and adhesion, deposition of extracellular matrix and epithelia to mesenchyme transition, properties of highly invasive cells. Analysis of castrated mice showed that the invasive phenotype driven by SOX9 is independent of androgen levels. Our study has identified a novel driver of prostate cancer progression and highlighted the cellular and molecular processes that are regulated by Sox9 to achieve invasive disease.
PreSET: Improving performance of phase change memories by exploiting asymmetry in write times

Phase Change Memory (PCM) is a promising technology for building future main memory systems. A prominent characteristic of PCM is that it has write latency much higher than read latency. Servicing such slow writes causes significant contention for read requests. For our baseline PCM system, the slow writes increase the effective read latency by almost 2X, causing significant performance degradation. This paper alleviates the problem of slow writes by exploiting the fundamental property of PCM devices that writes are slow only in one direction (SET operation) and are almost as fast as reads in the other direction (RESET operation). Therefore, a write operation to a line in which all memory cells have been SET prior to the write, will incur much lower latency. We propose PreSET, an architectural technique that leverages this property to pro-actively SET all the bits in a given memory line well in advance of the anticipated write to that memory line. Our proposed design initiates a PreSET request for a memory line as soon as that line becomes dirty in the cache, thereby allowing a large window of time for the PreSET operation to complete. Our evaluations show that PreSET is more effective and incurs lower storage overhead than previously proposed write cancellation techniques. We also describe static and dynamic throttling schemes to limit the rate of PreSET operations. Our proposal reduces effective read latency from 982 cycles to 594 cycles and increases system performance by 34%, while improving the energy-delay-product by 25%.
Nanometronomic treatment of 4T1 breast cancer with nanocaged doxorubicin prevents drug resistance and circumvents cardiotoxicity

Chemotherapeutic treatment of breast cancer is based on maximum tolerated dose (MTD) approach. However, advanced stage tumors are not effectively eradicated by MTD owing to suboptimal drug targeting, onset of therapeutic resistance and neoangiogenesis. In contrast, “metronomic” chemotherapy is based on frequent drug administrations at lower doses, resulting in neovascularization inhibition and induction of tumor dormancy. Here we show the potential of H-ferritin (HFn)-mediated targeted nanodelivery of metronomic doxorubicin (DOX) in the setting of a highly aggressive and metastatic 4T1 breast cancer mouse model with DOX-inducible expression of chemoresistance. We find that HFn-DOX administered at repeated doses of 1.24 mg kg−1 strongly improves the antitumor potential of DOX chemotherapy arresting the tumor progression. We find that such a potent antitumor effect is attributable to multiple nanodrug actions beyond cell killing, including inhibition of tumor angiogenesis and avoidance of chemoresistance. Multiparametric assessment of heart tissues, including histology, ultrastructural analysis of tissue morphology, and measurement of markers of reactive oxygen species and hepatic/renal conditions, provided evidence that metronomic HFn-DOX allowed us to overcome cardiotoxicity. Our results suggest that HFn-DOX has tremendous potential for the development of “nanometronomic” chemotherapy toward safe and tailored oncological treatments.