Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter 5 Electromagnetic Hypersensitivity

Electromagnetic hypersensitive persons (EHS) attribute their nonspecifi c health symptoms to environmental electromagnetic fi elds (EMF) of different sources in or outside their homes. In general, causal attribution is not restricted to specifi c EMF frequencies but involves a wide range from extremely low frequencies (ELF) up to radio frequencies (RF) including mobile telecommunication microwaves and radar. EHS argue that existing exposure limits were not low enough to account for their increased sensitivities. Results of measurement campaigns are summarized. They demonstrate that environmental fi elds in the ELF and RF range are usually orders of magnitudes below exposure limits. The rational and biological background of recommended exposure limits are described. The existing scientifi c studies are reviewed, including investigations on the prevalence of EHS among the general population, ability of EHS to perceive and/or react to exposures to weak EMF (assessed in laboratory provocational studies or to the vicinity of EMF sources studied by epidemiologic approaches), and the existence of a specifi c symptom cluster, which could characterize a suspected EHS syndrome, or individual EHSspecifi c factors such as electric perception thresholds, neurophysiologic parameters, and cognitive performance and behavior. However, in spite Chapter 5
Challenges of Future VANET and Cloud-Based Approaches

Vehicular ad hoc networks (VANETs) have been studied intensively due to their wide variety of applications and services, such as passenger safety, enhanced traffic efficiency, and infotainment. With the evolution of technology and sudden growth in the number of smart vehicles, traditional VANETs face several technical challenges in deployment and management due to less flexibility, scalability, poor connectivity, and inadequate intelligence. Cloud computing is considered a way to satisfy these requirements in VANETs. However, next-generation VANETs will have special requirements of autonomous vehicles with high mobility, low latency, real-time applications, and connectivity, which may not be resolved by conventional cloud computing. Hence, merging of fog computing with the conventional cloud for VANETs is discussed as a potential solution for several issues in current and future VANETs. In addition, fog computing can be enhanced by integrating Software-Defined Network (SDN), which provides flexibility, programmability, and global knowledge of the network. We present two example scenarios for timely dissemination of safety messages in future VANETs based on fog and a combination of fog and SDN. We also explained the issues that need to be resolved for the deployment of three different cloud-based approaches.
Mobility Fluctuation-Induced Low-Frequency Noise in Ultrascaled Ge Nanowire nMOSFETs With Near-Ballistic Transport

In this paper, we study the low-frequency noise in the Ge nanowire (NW) nMOSFETs with sub-100-nm channel length. The low-frequency noise with 1/ ${f}$ characteristics is proved to origin from the carriers’ mobility fluctuation. The dependences of low-frequency noise on NW geometry, channel length, equivalent oxide thickness (EOT), and channel doping concentration are examined by evaluating the Hooge parameters. It is shown that the low-frequency noise declines when the channel length of Ge NW nMOSFETs scales down, which is attributed to the electrons’ near ballistic transport. The electrons suffer more scatterings in the channels beneath the side walls of NWs or in the highly doped channels. The gate-oxide optimization is strongly demanded with the scaling down of EOT. Ultrascaled Ge NW nMOSFETs promise the enhancement of on-state performance and the suppression of low-frequency noise simultaneously.
CREATE: A Comprehensive Model for Instruction of Academic Language and Literacy in the Content Areas. CREATE Brief.

Center for Research on the Educational Achievement and Teaching of English Language Learners Introduction English learners continue to lag behind their Englishproficient peers in terms of academic achievement (National Center for Education Statistics, 2011). In addition, Hispanics, who make up the largest group of English learners in the United States, have the highest high school dropout rate in the country (Chapman, Laird, Ifill, & KewalRamani, 2011). As a response to this achievement gap and numerous other pressures, teachers are being challenged to teach to more rigorous standards, engage students with more complex text, and ensure that their students are college and career ready. At the same time, research on second language acquisition and best teaching practices for English learners, as reflected in the SIOP Model, calls on teachers to incorporate more peer interaction, visuals, hands-on experiences, prereading activities, and scaffolded writing assignments (Echevarría, Vogt, & Short, 2010). Teachers may find this recommendation for scaffolded learning to be in contradiction with district and state expectations for providing academic rigor and preparing students for independent performance on highstakes tests. The Center for Research on the Educational Achievement and Teaching of English Language Learners (CREATE) has responded to this challenge by integrating academic language development into the rigorous content area instruction of learners in the middle grades. This research brief is intended to explain instructional implications from the 7-year CREATE program of study as well as to guide practitioners in implementing the findings. School leaders who are interested in reforms that target academic language development within content area instruction to boost the achievement of both English learners and English-proficient students will benefit from the approach described in this brief. It will also be valuable for preservice and inservice teachers who are interested in practical techniques for creating scaffolded tasks in lesson plans that are aligned with grade-level content standards.
Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine

Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.
Critical Success Factors in Customer Relationship Management Implementation

The purpose of this study is to find the critical success factors of customer relationship management implementation in automobile industry. Semi-structured interviews were carried out to collect the needed data. The interviews were written or recorded then transcribed and analyzed by implying content analysis method. The results have reflected that all the investigated companies are implementing CRM furthermore some success factors such as training employees, top management support and the desired organizational culture have been determined that impacts the project significantly and intensely toward obtaining the desired results.
Microevolutionary selection dynamics acting on immune genes of the green‐veined white butterfly, Pieris napi

Insects rely on their innate immune system to successfully mediate complex interactions with their microbiota, as well as the microbes present in the environment. Previous work has shown that components of the canonical immune gene repertoire evolve rapidly and have evolutionary characteristics originating from interactions with fast‐evolving microorganisms. Although these interactions are likely to vary among populations, there is a poor understanding of the microevolutionary dynamics of immune genes, especially in non‐Dipteran insects. Here, we use the full set of canonical insect immune genes to investigate microevolutionary dynamics acting on these genes between and among populations by comparing three allopatric populations of the green‐veined white butterfly, Pieris napi (Linné; Lepidoptera, Pieridae). Immune genes showed increased genetic diversity compared to genes from the rest of the genome and various functional categories exhibited different types of signatures of selection, at different evolutionary scales, presenting a complex pattern of selection dynamics. Signatures of balancing selection were identified in 10 genes, and 17 genes appear to be under positive selection. Genes involved with the cellular arm of the immune response as well as the Toll pathway appear to be enriched among our outlier loci, regardless of functional category. This suggests that the targets of selection might focus upon an entire pathway, rather than functional subsets across pathways. Our microevolutionary results are similar to previously observed macroevolutionary patterns from diverse taxa, suggesting that either the immune system is robust to dramatic differences in life history and microbial communities, or that diverse microbes exert similar selection pressures.
Hierarchical Meta-Analysis: A Simulation Study Comparing Classical Random Effects and Fully Bayesian Methods

HIERARCHICAL META-ANALYSIS: A SIMULATION STUDY COMPARING CLASSICAL RANDOM EFFECTS AND FULLY BAYESIAN METHODS by Nancy R. Andiloro Advisor: David Rindskopf Meta-analytic data have a natural hierarchical structure to them, where individuals are nested within studies, and have both within-and between-study variation to model. A random-effects hierarchical linear model is useful to conduct a meta-analysis because it allows one to appropriately parse out the two components of variation that exist within and across studies to determine an observed effect. Empirical Bayes estimation considers the reliability of variance estimates; when the reliability of the effect size estimate for a study is high, substantial weight is placed on that estimate. However, problems with estimation arise when the number of studies and their sample size is small. Although time-consuming to employ, fully Bayesian methods offer a solution, but few studies systematically compare random-effects to fully Bayesian methods. A simulation study was performed varying certain characteristics of meta-analyses, such as the number of studies, their sample size and level of heterogeneity across studies, to determine under which condition(s) a fully Bayesian method improves meta-analytic findings. Results are unexpectedly inconsistent, whereby certain scenarios in which the number of studies is small and level of heterogeneity large, show that empirical Bayes performs better than the fully Bayesian method. Despite this, bias and mean-squared error are lower, on average, among the fully Bayesian models, with a model specifying a Cauchy prior on τ performing best for the most favorable scenario. Implications and areas for future study are discussed.
Raman Spectroscopy for Inverted Papilloma: A Proof-of-Concept Study

Inverted papillomas are tumors of the sinonasal tract with a propensity to recur. Raman spectroscopy can potentially identify inverted papillomas from other tissue based on biochemical signatures. A pilot study comparing Raman spectroscopy to histopathology for 3 types of sinonasal tissue was performed. Spectral data of biopsies from patients with normal sinonasal mucosa, chronic rhinosinusitis, and inverted papillomas are compared to histopathology using principal component analysis and linear discriminant analysis after data preprocessing. A total of 18 normal, 15 chronic rhinosinusitis, and 18 inverted papilloma specimens were evaluated. The model distinguished normal sinonasal mucosa, chronic rhinosinusitis, and inverted papilloma tissue with an overall accuracy of 90.2% (95% confidence interval, 0.86-0.94). In conclusion, Raman spectroscopy can distinguish inverted papilloma, normal sinonasal mucosa, and chronically rhinosinusitis tissue with acceptable accuracy.
Language adaptation experiments via cross-lingual embeddings for related languages

Language Adaptation (similarly to Domain Adaptation) is a general approach to extend existing resources from a better resourced language (donor) to a lesser resourced one (recipient) by exploiting the lexical and grammatical similarity between them when the two languages are related. The current study improves the state of the art in cross-lingual word embeddings by considering the impact of orthographic similarity between cognates. In particular, the use of the Weighted Levenshtein Distance combined with orthogonalisation of the translation matrix and generalised correction for hubness can considerably improve the state of the art in induction of bilingual lexicons. In addition to intrinsic evaluation in the bilingual lexicon induction task, the paper reports extrinsic evaluation of the cross-lingual embeddings via their application to the Named-Entity Recognition task across Slavonic languages. The tools and the aligned word embedding spaces for the Romance and Slavonic language families have been released.
Examining the Impact of Afterschool STEM Programs.

Recent years have seen a growing recognion that social and economic factors play a crucial role in influencing academic success and that young people require supports that extend beyond the school walls. The noon of a " learning ecosystem " is taking root, a concept that places students at the center, with resources and supports organized around them. In such a system, schools are extremely important but are just one of many influences in a young person's life. In addion to schools, the ecosystem includes the influence of families and peers; out‐of‐school‐‐me offerings such as aerschool programs; and community resources such as science centers, libraries and media. Aerschool programs have long aimed to posively influence students' personal development and support their social and emoonal growth. Studies of high‐quality aerschool programs have found that parcipang children see a significant improvement in their self‐percepon, increased posive social behavior and a decrease in problem behaviors—changes that ulmately extend to school‐related behavior. Hence, aerschool programs are increasingly seen as a key social and academic support for youth. Aerschool researchers and providers have recognized that hands‐on, inquiry‐driven science, technology, engineering and math (STEM) programs are in line with aerschool's overall approach to educaon and have increasingly begun to include STEM in their aerschool offerings. Aerschool programs that provide Examining the impact of aerschool STEM programs | 1 strong STEM learning experiences are making an impact on parcipang youth—youth not only become excited and engaged in these fields but develop STEM skills and proficiencies, come to value these fields and their contribuons to society, and—significantly—begin to see themselves as potenal contributors to the STEM enterprise.  Program aendance and engagement in the 4‐H Tech Wizards program is high—on average 95 percent of enrolled youth aend sessions regularly and 95 percent of parcipants stayed in the program for three years to build successively on their tech skills.  Girlstart Aer School parcipants engage weekly in rigorous problem‐solving. Using inquiry and iterave design, they generate predicons and hypotheses, document observaons, and prototype soluons. At the end of the year, 91 percent of parcipants demonstrated mastery of scienfic inquiry and the engineering design process.  Every week at Science Club, an aerschool program run as a partnership between Northwestern University and the Boys & Girls Club of Chicago, youth work alongside scienst mentors on fun, challenge‐based curricula. These units focus on health and biomedical careers and development of scienfic …
A Software-Defined QoS Provisioning Framework for HPC Applications

With the emergence of large-scale data-intensive high-performance applications, new I/O challenges appear in the efficient management of petabytes of information in High-Performance Computing (HPC) environments. Data management environments must meet the performance needs of such applications, represented by various Quality-of-Service (QoS) metrics such as desired bandwidth, response time guarantee, and resource utilization. Traditional high-performance management platforms are facing considerable challenges regarding flexibility, as well as the need to address a variety of QoS metrics and constraints. To tackle these challenges, a Software-Defined approach is considered promising, and various prototypes have already been deployed in Cloud-based data centers. In this paper, we investigate the idea of utilizing a software-defined approach to provide I/O QoS provisioning for HPC applications. We identify the key challenges towards the high degree of concurrency and variation in HPC platforms, and propose a series of novel designs into the general software-defined approach in order to deliver our goal. Specifically, we introduced a borrowing-based strategy and a new M-LWDF algorithm based on traditional token-bucket algorithms to assure a fair and efficient utilization of resources for HPC applications. Due to the lack of software-defined frameworks in current HPC platform, we evaluated our framework through simulation. The experimental results show that our strategies make a significant improvement upon the general HPC frameworks and lead to clear performance gain for HPC applications.
Combination chemotherapy with gemcitabine, oxaliplatin, and paclitaxel in patients with cisplatin-refractory or multiply relapsed germ-cell tumors: a study of the German Testicular Cancer Study Group.

BACKGROUND The aim of this study is to determine feasibility and efficacy of the combination regimen gemcitabine, oxaliplatin, and paclitaxel (GOP) in patients with cisplatin-refractory or multiply relapsed germ-cell tumors. PATIENTS AND METHODS From April 2003 to October 2006, 41 patients refractory to cisplatin-based chemotherapy or with relapse after high-dose chemotherapy (HDCT) plus stem-cell support (peripheral blood stem-cell transplantation: PBSCT) received 800 mg/m2 gemcitabine, 80 mg/m2 paclitaxel (Taxol), both on days 1 + 8, and oxaliplatin 130 mg/m2 on day 1 of a 3-week cycle for a minimum of two cycles. Primary end point was response rate. Patients were pretreated with a median of two lines of platin-based chemotherapy (range, 1-3), and 78% had relapsed after HDCT/PBSCT. RESULTS Seventy-three percent of patients had relapsed within 3 months after the last cisplatin-based chemotherapy. Five percent of the patients achieved a complete response, and 34% and 12% a marker-negative and marker-positive partial response, respectively (overall response rate 51%). After a median follow-up of 5 months (range, 0-20), 15% of the patients remain in complete remission after GOP chemotherapy +/- residual tumor resection with a median response duration of 8 months (1 to 17+). Main toxicity was leucocytopenia grade 3/4 in 15%, anemia in 7%, and thrombocytopenia in 49% of the patients. CONCLUSION Combination chemotherapy with GOP is feasible and effective with acceptable toxicity in patients with treatment-refractory germ-cell tumors.
Evolution of 'maleness' and outcrossing in a population of the self-fertilizing killifish, Kryptolebias marmoratus

Question: Does the persistently high frequency of males in the Twin Cays population of Kryptolebias (formerly Rivulus) mamoratus (Pisces: Rivulidae), a self-fertilizing, androdioecious species, result from ecophenotypic effects or genetic divergence from other populations? Hypothesis: Because males are easily produced in the laboratory by temperature manipulations of embryos or juveniles, their frequency in this population is environmentally induced. Methods: Common garden experiment, two generations. Conclusions: Genetic differences exist between the Twin Cays population and other populations in the tendency to produce males. Since males likely induce androdioecious outcrossing, and the Twin Cays population is not ancestral to others, this genetic difference may indicate a shift from predominant selfing to outcrossing, a direction not predicted by current theory.
Efficiency and labour market polarisation

The knowledge economy gets a reasonably clean bill of health as far as polarisation between "good" and "bad" jobs is concerned. Overall Rececca Fauth and Ian Brinkley agree with recent analyses positing a stable labour market and continued expansion of well-paid jobs at the top of the labour market. With the exception of some remaining job polarisation for men, their findings stand in contrast to the hourglass economy story from the 1980s that stemmed from deindustrialisation and the disappearing middle class.
Improved Glycemic Control With Minimal Change in Medication Regimen Complexity in a Pharmacist-Endocrinologist Diabetes Intense Medical Management (DIMM) “Tune Up” Clinic

Background: Gaining glycemic control in patients with type 2 diabetes (T2D) usually requires more complicated medication regimens. Increased medication regimen complexity (MRC) negatively impacts adherence and clinical outcomes. Objective: Compare MRC change in patients with uncontrolled T2D referred to a collaborative pharmacist-endocrinologist Diabetes Intense Medical Management (DIMM) clinic “tune up” model versus similar patients receiving usual primary care provider (PCP) care over 6 months. Methods: Retrospective, observational, comparative cohort study compared MRC of complex DIMM clinic patients to a similar group (adults with T2D, glycosylated hemoglobin [A1C] ≥8%), continuing to receive usual care from their PCPs. The MRC Index (MRCI) was used to quantify MRC. Results: Both DIMM (n=99) and PCP (n=56) groups were similar, with high baseline mean MRC scores as measured by number of medications and MRCI (12.0 [SD=5.7] vs 13.7 [SD = 5.6], and 32.7 [SD=17.0] vs 38 [SD=16.5]), respectively. Mean MRC change over 6 months was not significantly different between groups, although mean A1C reduction was significantly greater in the DIMM versus PCP group (−2.4% [SD=2.1] vs −0.8% [SD=1.7], P<0.001, respectively). Conclusions and Relevance: Outcomes represent the first report demonstrating how treating patients with an innovative DIMM model can help complex T2D patients achieve glycemic control without increasing the MRC to more than a comparator group. With the growing prevalence of T2D and associated elevated treatment costs, identifying effective means for achieving glycemic control without increasing complexity is needed. Application of this model may be considered by other health systems to aid in achieving outcome measures.