Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of a Synthetic Cannabinoid in a Correctional Population for Posttraumatic Stress Disorder–Related Insomnia and Nightmares, Chronic Pain, Harm Reduction, and Other Indications

Abstract Nabilone is a synthetic cannabinoid that has shown promise for the treatment of posttraumatic stress disorder (PTSD)–related insomnia and nightmares as well as efficacy in the management of chronic pain. It has also been proposed for harm reduction in cannabis dependence. Its effectiveness for management of concurrent disorders in seriously mentally ill correctional populations has not been evaluated. This retrospective study of 104 male inmates with serious mental illness prescribed nabilone analyzes the indications, efficacy, and safety of its use. Medications discontinued with the initiation of nabilone were also reviewed. The results showed nabilone targeting a mean of 3.5 indications per patient, thus likely reducing polypharmacy risk. The mean final dosage was 4.0 mg. Results indicated significant improvement in PTSD-associated insomnia, nightmares, PTSD symptoms, and Global Assessment of Functioning and subjective improvement in chronic pain. Medications associated with greater risk for adverse effects or abuse than nabilone were often able to be discontinued with the initiation of nabilone, most often antipsychotics and sedative/hypnotics. There was no evidence of abuse within this high-risk population or reduction of efficacy when nabilone was given in powder form with water rather than as a capsule. This study supports the promise of nabilone as a safe, effective treatment for concurrent disorders in seriously mentally ill correctional populations. Prospective, randomized controlled trials are required to confirm our preliminary results. Follow-up in the community will be required to confirm effectiveness in harm reduction.
Transfers of marketing knowledge in acquisitions

Knowledge transfers are an important element of international market entry and can be a significant source of value creation in acquisitions. However, an acquisition’s own dynamics may impede these transfers and thereby also the realisation of potential transfer benefits. This study will, therefore, examine a number of likely influences on transfer success as well as the impact of active and ongoing knowledge transfer on marketing performance.
Advanced Interactions with Heatmaps for Analyzing High-Dimensional Datasets

We introduce an extended heatmap visualization integrated with enhanced interactive capabilities and computational tools for analyzing large and complex datasets. A heatmap is capable of displaying a large amount of data with many dimensions while minimizing graphic area. Varying levels of detail are provided by rendering cells as data values or computed values. Earlier approaches of having peer interfaces with R or other mathematical and analytic environments were powerful, but these were slower and lacked more interactive visual control and feedback. By including built-in computational tools, a variety of useful functions are made available to the user to enable quick identification of interesting patterns and relationships in a more guided exploratory environment. In a case study, we demonstrate the usefulness of this new visualization to solve problems related to drug discovery. Index Terms — Visual analytics, interaction techniques, large data visualization, multidimensional, multi-variate.
Domain of attraction of the quasi-stationary distributions for the Ornstein-Uhlenbeck process

Let (X t ) be a one-dimensional Ornstein-Uhlenbeck process with initial density function f: R + → R + , which is a regularly varying function with exponent -(1 + η), η ∈ (0, 1). We prove the existence of a probability measure v with a Lebesgue density, depending on η, such that for every A E B(R + ): formula math.
Freshman or Fresher? Quantifying the Geographic Variation of Internet Language

We present a new computational technique to detect and analyze statistically significant geographic variation in language. Our meta-analysis approach captures statistical properties of word usage across geographical regions and uses statistical methods to identify significant changes specific to regions. While previous approaches have primarily focused on lexical variation between regions, our method identifies words that demonstrate semantic and syntactic variation as well. We extend recently developed techniques for neural language models to learn word representations which capture differing semantics across geographical regions. In order to quantify this variation and ensure robust detection of true regional differences, we formulate a null model to determine whether observed changes are statistically significant. Our method is the first such approach to explicitly account for random variation due to chance while detecting regional variation in word meaning. To validate our model, we study and analyze two different massive online data sets: millions of tweets from Twitter spanning not only four different countries but also fifty states, as well as millions of phrases contained in the Google Book Ngrams. Our analysis reveals interesting facets of language change at multiple scales of geographic resolution -- from neighboring states to distant continents. Finally, using our model, we propose a measure of semantic distance between languages. Our analysis of British and American English over a period of 100 years reveals that semantic variation between these dialects is shrinking.
New Automatic Layout Method based on Magnetic Spring Model for Object Diagrams of OMT

We propose to apply Magnetic Spring Model for arranging object diagrams of OMT. The main characteristics of our automatic layout method are: efficient space utilization; arranging connected classes nearer to each other; and keeping the meaning of relationships in the diagram. We carried out experiments to compare the new method and the existing ones. In our layout method, most of the nodes are arranged at the position where users expect to, and users' thinking time of our method is shorter than the existing methods. Our layout method is useful to draw object diagrams by the graphical editor of OMT CASE tools.
Tumor Suppressor Gene Inactivation during Cadmium-Induced Malignant Transformation of Human Prostate Cells Correlates with Overexpression of de Novo DNA Methyltransferase

Background Aberrant DNA methylation is common in carcinogenesis. The typical pattern appears to involve reduced expression of maintenance DNA methyltransferase, DNMT1, inducing genomic hypomethylation, whereas increased expression of de novo DNMT3a or 3b causes gene-specific hypermethylation. Objectives During cadmium-induced malignant transformation, an unusual pattern of genomic hypermethylation occurred that we studied to provide insight into the roles of specific DNMTs in oncogenesis. Methods Gene expression and DNA methylation were assessed in control and chronic cadmium-transformed prostate epithelial cells (CTPE) using reverse transcription–polymerase chain reaction (RT-PCR), Western blot analysis, methylation-specific PCR, and methyl acceptance assay. Results During the 10-weeks of cadmium exposure that induced malignant transformation, progressive increases in generalized DNMT enzymatic activity occurred that were associated with over-expression of DNMT3b without changes in DNMT1 expression. Increased DNMT3b expression preceded increased DNMT enzymatic activity. Procainamide, a specific DNMT1 inhibitor, reversed cadmium-induced genomic DNA hypermethylation. Reduced expression of the tumor suppressor genes, RASSF1A and p16, began about the time DNMT3b overexpression first occurred and progressively decreased thereafter. RASSF1A and p16 promoter regions were heavily methylated in CTPE cells, indicating silencing by hypermethylation, while the DNA demethylating agent, 5-aza-2′-deoxycytidine, reversed this silencing. DNMT1 inhibition only modestly increased RASSF1A and p16 expression in CTPE cells and did not completely reverse silencing. Conclusions These data indicate that DNMT3b overexpression can result in generalized DNA hypermethylation and gene silencing but that DNMT1 is required to maintain these effects. The pattern of genomic DNA hypermethylation together with up-regulation of DNMT3b may provide a unique set of biomarkers to specifically identify cadmium-induced human prostate cancers.
Hodgkin's lymphoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.

Pathological diagnosis should be made according to the World Health Organization (WHO) classification from a sufficiently large surgical specimen or excisional lymph node biopsy to provide enough material for fresh frozen and formalin-fixed samples. Classical Hodgkin lymphoma (cHL) includes nodular sclerosing (NS), mixed cellularity (MC), lymphocyte-rich (LR) and lymphocyte-depleted (LD) subtypes and represents 95% of all HL cases. It is distinguished from nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) which accounts for 5% of all HL cases.
A Simple Gamma Random Number Generator for Arbitrary Shape Parameters

This paper proposes an improved gamma random generator. In the past, a lot of gamma random number generators have been proposed, and depending on a shape parameter (say, alpha) they are roughly classified into two cases: (i) alpha lies on the interval (0,1) and (ii) alpha is greater than 1, where alpha=1 can be included in either case. In addition, Cheng and Feast (1980) extended the gamma random number generator in the case where alpha is greater than 1/n, where n denotes an arbitrary positive number. Taking n as a decreasing function of alpha, in this paper we propose a simple gamma random number generator with shape parameter alpha greater than zero. The proposed algorithm is very simple and shows quite good performance.
Taking up the RoCKIn @ Work Object Recognition Challenge With The Bag of Keypoints Approach

This research project addresses the problem of object-classification by a robot in an industrial context. Solving this problem brings industrial robots one step closer to being able to operate autonomously and eventually to reproduce themselves. The approach described in this thesis enables a system to distinguish classes of objects using RGB data only, which can be a difficult task when the classes are similar. Other approaches have been to compare generic features of objects to classify them, and to build histograms of more distinct features. By performing experiments I was able to determine some specific parameters for our problem and combine different types of input features. By experimenting with different classification techniques, error-rates of nearly 22% for object type and 11% for object category were reached.
Leading school for learning: principal practices in Taiwan

Purpose The purpose of this paper is to discuss how principals in Taiwan lead student and teacher learning at a time of leadership and learning paradigm shifts and the imminent implementation of the curriculum guideline for 12-year basic education. Design/methodology/approach This study interviewed 32 elementary and junior high school principals purposively sampled based on reputation and recommendation from senior principals and government officials. Findings As a society which values credentialism, principals in Taiwan face challenges in executing the vision of educating student as a whole person. The authors discuss how principals are solidifying whole person education as the espoused value, how they are enforcing school-based curriculum and effective instruction, and encouraging teacher professional learning. Principals are sharing power by recruiting stakeholders’ participation in guiding school development and enacting distributed leadership, while also building relationship as social capital and soliciting support from the community to establish the conditions to improve teaching and learning. Research limitations/implications This paper highlights how principal practices are evolving in a time of changing conception of learning from academic achievement to multiple competencies and the shifting paradigm of power from participatory decision making to distributed leadership. This paper ends with a discussion on how leadership for learning (LfL) as a community engagement has emerged. Practical implications With the shifting of the concept and paradigm of learning, principals in a high power distance society like Taiwan are now facing opportunities as well as challenges to lead teachers to engaging students in inquiry and collaboration. Originality/value This paper highlights the indigenous practices of principal LfL in a high-performing East Asian education system in a time of changing notions of learning and leadership.
Visualisation and Analysis of Students' Interaction Data in Exploratory earning Environments

Log files from adaptive Exploratory Learning Environments can contain prohibitively large quantities of data for visualisation and analysis. Moreover, it is hard to know in advance what data is required for analytical purposes. Using a microworld for secondary algebra as a case study, we discuss how students' interaction data can be transformed into a data warehouse in order to allow its visualisation and exploration using online analytical processing (OLAP) tools. We also present some additional, more targeted, visualisations of the students' interaction data. We demonstrate the possibilities that these visualisations provide for exploratory data analysis, enabling confirmation or contradiction of expectations that pedagogical experts may have about the system and ultimately providing both empirical evidence and insights for its further development.
Tuning the low cut-off frequency in multichannel neural recording amplifiers by the on-chip correction DACs

This paper presents a design and measurements of multichannel integrated circuits dedicated to recording of neurobiological signals. 64 recording channels have been implemented in a single chip using a commercially available CMOS 180 nm process. A single recording amplifier consumes only 25 µW from 1.8 V supply and occupies 0.13 mm2 of the silicon area. Its main parameters such as the low/high cut off frequencies and the voltage gain are controlled thanks to the on-chip register. User is able to change the low cut off frequency in the 60 mHz – 100 Hz range in each channel independently while the high cut off frequency and the voltage gain can be set to 4.7 kHz / 12 kHz and 139 V/V / 1100 V/V respectively. The input referred noise depends on the bandwidth of the recording channel and is equal to 3.7 µV (100 Hz – 12 kHz) or to 7.6 µV (3 Hz – 12 kHz). This paper deals with problems that are present in a multichannel integrated recording electronics for neurobiology experiments such as: ability to record input signals in the frequency range below a single Hz, and the spread of the cut off frequencies from channel to channel in such systems. Up to our knowledge the solution presented in this paper is the first one reporting the multichannel IC that is able both to record extremely low frequency signals in each channel with a small spread of this parameter from channel to channel.
S100A8 and S100A9 Positive Cells in Colorectal Carcinoma: Clinicopathological Analysis

Introduction. In colorectal carcinoma, tumoral tissues infiltrate with various immune/inflammatory cells along their invasive margins and the increased S100A8/A9 expression in these immune cells infiltrating the tumor has recently been demonstrated. We examined S100A8/A9 as a potential therapeutic target in the treatment of colorectal carcinoma. Materials and Methods. The current study included a sample of 80 patients diagnosed with CRC (30 cases with distant metastasis, 30 cases with lymph node metastasis, and 20 cases with no metastasis). Peritumoral and intratumoral S100A8 and S100A9 expressing inflammatory cells were counted in primary tumors and their metastasis and correlated with clinicopathological parameters. Results. The peritumoral and intratumoral S100A8/A9 positive cells showed no correlation with age, gender, or depth of tumor invasion. However higher counts of peritumoral and intratumoral S100A8/A9 positive cells were associated with larger tumor size, higher grade, and the presence of metastasis (P < 0.05). Conclusion. Our study also found significantly higher number of S100A8/A9 positive cells in the tumor microenvironment among patients with large tumor size, high grade, and metastatic disease. Moreover, in our study, we observed that the expression in the tumor metastasis appeared similar to that of primary tumor.
Testing for Unit Roots in Semiannual Data

We consider the problem of testing for unit roots at the zero and seasonal frequencies in timeseries data which are recorded semi-annually. The proposed methodology follows that of Hylleberg et al. (1990) and Beaulieu and Miron (1993) for quarterly and monthly data respectively. The non-standard asymptotic distributions for the single and joint tests are derived, and various percentiles of the finite-sample distributions are tabulated. Monte Carlo simulation is used to investigate the powers of the tests, and we illustrate their application to several semiannual economic time-series. JEL classifications: C12, C22
A Fuzzy Logic-Based Buffer Overflow Vulnerability Auditor

Buffer overflow (BOF) vulnerabilities in programs might result in unwanted consequences such as neighboring data corruption and execution of arbitrary code. To assure that implemented programs are free from BOF, auditing is a well known quality assurance method. Today, there exist few tools that aid an auditor to partially automate the task of BOF vulnerability auditing. These tools provide too many warnings that are often similar types to be dealt with and do not allow an auditor providing his/her opinions to better interpret the generated warnings. To improve the quality of warnings, we propose a fuzzy logic-based BOF vulnerability auditor. Our contribution includes the development of crisp BOF vulnerability characteristics and the corresponding fuzzy sets. We apply Mamdani style fuzzy inferences by developing sets of rules to infer the presence of BOF warning present in programs. Moreover, for the overall assessment of a program's vulnerability level, we design a multi-unit fuzzy logic-based system. The auditor has been evaluated with benchmark programs that contain BOF vulnerabilities. The results show that our auditor performs better compared to the existing auditing tools. The auditor can be used as a basis to assure the quality of a program against BOF vulnerabilities.
Towards a Descriptive Depth Index for 3D Content: Measuring Perspective Depth Cues

3D quality of experience (QoE) in nature is a multidimensional problem and involves many factors that contribute to the global quality rating such as image quality, depth perception and visual discomfort. One important aspect for the development and evaluation of 3D processing techniques is the selection of appropriate 3D content. To this aim it is necessary to develop computational methods that can automatically measure the 3D characteristics of a scene, similar to the spatial and temporal information indices commonly used for assessing 2D content. The presented work is one step in the development of such a depth index (DI) which will target the evaluation of the depth-related characteristics of 3D video sequences. The paper focuses on the linear perspective as one of the major monocular depth cues. It compares two distinct approaches for measuring the strength of perspective depth cues and analyzes their limits on a 2D image dataset with associated subjective ratings.
Not truly partnerless: Non-residential partnerships and retreat from marriage in Spain

In Spain, nearly two-thirds of women aged 20-34 have not yet entered their first union. However, almost half of them have a stable partner in a different household. Hence, the drop in marriage rates and low prevalence of cohabitation cannot be rightly interpreted as a decline in partnership formation, but rather as a postponement of co-residential unions. This paper examines the prevalence and determinants of non-residential stable partnerships among young adults (women aged 20-34), in relation to cohabitation and marriage, using a multinomial logit model of current partnership type. The analysis is based on data from the 1999 Spanish Fertility Survey.
Layout-aware synthesis of arithmetic circuits

We propose a new module generation/synthesis algorithm for arithmetic circuits utilizing carry-save-adder (CSA) modules, which not only optimizes the circuit timing but also generates a much more regular interconnect topology of the final circuits. Specifically, we propose a two-step algorithm. In Phase 1 (CSA module generation), we propose an optimal-timing CSA module generation algorithm for an arithmetic expression under a general CSA timing model. In Phase 2 (Bit-level interconnect refinements), we optimally refine the interconnects between the CSA modules while retaining the global CSA-tree structure produced by Phase 1. It is shown that the timing of the circuits produced by our approach is equal or close to that obtained in most test-cases (even without including the interconnect delay), and at the same time, the interconnects in the layout are significantly shorter and more regular.
N-gram based paraphrase generator from large text document

This paper describes the paraphrase generation based on n-gram approach. N-grams are relevant words of text document that can be applied for a range of Natural Language Processing (NLP) applications. The candidate paraphrases are generated based on trigrams approach. The reference paraphrases (keyphrases) are the set of relevant paraphrases, which acts like training data set for generating candidate paraphrases. The task of paraphrase generation is similar to machine translation; hence we used machine translation evaluation metrics. R-precision evaluation metric is used to find the number of common words between candidate and reference paraphrases.
Multidimensional SME Performance Evaluation: Upgrading to Data Warehousing & Data Mining Techniques

We present a fully implemented expert diagnostic system which evaluates the performance of SMEs on a benchmarking basis. The system has been in use for several years and has gone through a constant and quite challenging evolution in order to meet both the needs of research and the production of benchmarking reports. We discuss why we decided to upgrade our system with data warehousing and data mining techniques. At the time of writing, we are about to activate the new data warehouse and start our experimentations with data mining techniques—newest results will be available when the conference will be held. We think data warehousing and data mining will allow us to significantly extend our knowledge on SMEs, and further improve our performance evaluation model.
General to Specific Modelling of Exchange Rate Volatility: A Forecast Evaluation

The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications are especially valuable in conditional forecasting, since the specification that employs actual values on the uncertain information performs particularly well.