Miracle-dz/UniFAR-FTUs huggingface dataset:
Short–Term Fetal Heart Rate Variation, Decelerations, and Umbilical Flow Velocity Waveforms Before Labor

Objective To determine the value of computerized antepartum measurements of short–term fetal heart rate (FHR) variation and decelerations as a predictor of outcome, and to compare these with measurements of the umbilical artery flow velocity waveform. Methods Data were collected from 3563 high–risk patients for measurements of FHR variables (15,702 records) and outcome (intrauterine death or metabolic acidemia on delivery). Detailed analyses were made on 89 patients with one or more records in which short–term FHR variation was 3 milliseconds or less. Umbilical artery flow velocity waveforms were measured concurrently on 2441 occasions in 991 patients. Results More than half of the patients with FHR variation of 3 milliseconds or less were identified before 31 weeks. When short-term FHR variation exceeded 3 milliseconds, there were no intrauterine deaths and only one instance of metabolic acidemia on cesarean delivery. When FHR variation fell below 2.6 milliseconds, 34% of the subjects had metabolic acidemia on cesarean or intrauterine death. The appearance or absence of decelerations was an unreliable guide to outcome. The correlation between FHR variation and the umbilical artery flow velocity waveform was low (r =0.32). The population studied contained some patients without placental vascular disease or, in five with preeclampsia, without abnormal umbilical artery velocity waveforms but with grossly reduced FHR variation. Conclusion Reduction in short–term FHR variation, as measured by computer, reliably predicts fetal outcome and is a more general measure of fetal well–being than are umbilical artery flow velocities.
Effectiveness of a handwriting readiness program in head start: a two-group controlled trial.

OBJECTIVE This study measured skill improvement in prewriting skills, kindergarten readiness, first-name writing, and handwriting-nonspecific fine motor skills of students at Head Start who participated in Handwriting Without Tears-Get Set for School (HWT-GSS) programming. METHOD We conducted a two-group, nonrandomized controlled trial using a pretest-posttest design at a rural Head Start. The effectiveness of adding the HWT-GSS curriculum in one preschool classroom was compared with a control classroom. RESULTS On posttesting, the experimental group made significant improvements compared with the control group in prewriting, kindergarten readiness, and fine motor skills. Both groups made significant improvements between pretesting and posttesting in prewriting, first name writing, and school readiness. CONCLUSION Adding HWT-GSS to the Head Start program would be beneficial in improving handwriting readiness skills.
Revenge Versus Forgiveness/Forbearance in Response to Narrative-Simulated Victimization

The authors engaged men and women (N = 120) who read one of two versions of a dramatic narrative in which the narrator became HIV-positive following heterosexual intercourse with an AIDS-infected partner. Assuming the role of the narrator, the participants completed two situation-instigated criterion measures as a response to becoming HIV-infected, indicated whom they blamed for their predicament, and completed two "trait" predictor measures—negative affect and response to perceived victimization in everyday life. Trait victimization response and blaming the sexual partner were strongly associated with high rather than low negative affect. Reasons for the reluctance to blame the sexual partner and seek revenge were discussed, and recommendations were made to develop less problematic simulated victimization narratives.
H I in Early-Type Galaxies. II. Mass Loss and Galactic Winds

In the course of the discussion we summarize several observations which appear to follow logically from the existence of galactic winds: (1) lack of interstellar matter in most early-type galaxies, (2) the existence of young stars and dust in luminous dwarf ellipticals like NGC 205, (3) the fact that radio activity is associated preferentially with massive elliptical galaxies, (4) X-ray sources in clusters of galaxies, and (5) the observed dependence of elliptical metallicity on galaxy mass (Larson 1974b). (AIP)
Selective Extraction of Uranium from a Mixture of Metal or Metal Oxides by a Tri-n-butylphosphate Complex with HNO_3 and H_2O in Supercritical CO_2

In order to study the decontamination nature of the reactive extraction of uranium in the presence of some metal chemicals using a single-phase mixture of HNO_3, H_2O and tri- n -butylphosphate (TBP) in supercritical carbon dioxide (SC-CO_2), we measured the decontamination factors (DFs) of Sr, Zr, Mo, Ru, Pd, Ce and Nd from their mixture with U. These elements were originally added to U_3O_8 as SrO, ZrO_2, MoO_3, RuO_2, Pd, CeO_2 and Nd_2O_3, and the extraction was performed at 18 MPa and 323 K with the single-phase mixture. The DFs for these elements were determined to be greater than 10^3 when the molecular ratio of U to TBP in the extracted complex was greater than 0.3. Dilution by SC-CO_2 effectively increased the DFs.
Fault-reconstruction-based cascaded sliding mode observers for descriptor linear systems

This paper develops a cascaded sliding mode observer method to reconstruct actuator faults for a class of descriptor linear systems. Based on a new canonical form, a novel design method is presented to discuss the existence conditions of the sliding mode observer. Furthermore, the proposed method is extended to general descriptor linear systems with actuator faults. Finally, the effectiveness of the proposed technique is illustrated by a simulation example.
A Social Robot for Facilitating Human Relations in Smart Environments

This paper describes how a robot may use social network analysis measures for facilitating social relations when acting as a “host” in a smart environment. The robot’s main goal consists in welcoming people, facilitating contacts and information sharing among people present in the environment. It uses knowledge on the structure of the social network for selecting the most appropriate strategy to create new relations or to spread information in the most effective way. To this aim, a multiagent system has been implemented for simulating and evaluating the functioning of the social facilitator.
IMPACT OF TRADE LIBERALIZATION AND DOMESTIC ECONOMIC REFORMS ON TECHNICAL EFFICIENCY OF AGRO-BASED INDUSTRIES IN PAKISTAN

Pakistan introduced a package of economic reforms consisting of liberalization, deregulation and privatization policies. The main focus of these reforms was on achieving macroeconomic stability and a reasonable rate of economic growth. Manufacturing sector is an important sector of the economy of Pakistan and contributes about 25% share in GDP. Agro-based industries have a special importance in Pakistan because these industries are the main source of foreign exchange earnings and employment. Presently these industries operate under imperfect market conditions and have high levels of inefficiency. The development of these industries is closely linked with the overall development of the country. The spillover effects are assumed to be very large for other industries in general and the agricultural sector in particular. The purpose of this paper is to evaluate the impact of trade related domestic reforms and openness on technical efficiency of the agro-based industries. Our analysis shows a favorable impact of trade related reforms on the efficiency level of agro-based industries.
Applying Feature Selective Validation method to quantify EM indoor location system

Accurate location system using electromagnetic sensors is one of the effective solutions being used in indoor position applications. Non-linearity of data have important influence on accuracy of location system. We proposed the mapping algorithm that calibrates data received by EM sensors and realized high accuracy around 1cm. In order to quantify performance of mapping algorithm to real time EM recorded data, we defined the point to point error distance, its distribution at different heights/radius and adopt Feature Selective Validation method to test the performance of the algorithm. We presents the effectiveness of calibration algorithm in indoor positioning system based on EM sensors by the interpretation of FSV results.
A Rorschach Study of Oral Dependence in Alcoholics and Depressives

Despite the strong association between alcoholism and orality in psychoanalytic theory, use of the Rorschach Inkblot Test to provide empirical support for such a link has yielded decidedly mixed results. However, Masling's Rorschach Oral-Dependency (ROD) scale has shown twice that people with alcoholism give more oral-dependent responses on the Rorschach than matched comparison groups (Bertrand & Masling, 1969; Weiss & Masling, 1970), which is supportive of classical analytic theory. In this study, we investigated alcohol groups, depression groups, and "normal" undergraduates with the ROD scale and found that the 2 clinical groups produced higher ROD scores than the undergraduates. In addition, recent studies by Duberstein and Talbot (1993) and Fowler, Hilsenroth, and Handler (1996) provide evidence for an object relations model of dependency that suggests that a balance between anaclitic dependence and complete independence, in which dependency needs are acknowledged but are not overwhelming, is most adaptive. This model of dependency was evaluated; it was found that a simple difference in group means provided a better fit with the data, although some evidence of an object relations model also was found. Finally, Rorschach and MMPI-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) levels of general defensiveness and primary process manifestations in Rorschach content were investigated to assess whether participants were responding defensively to the testing and whether there were any differences in the nature of oral-dependent responses between the clinical groups.
A Novel Approach for Handling Imbalanced Data in Medical Diagnosis using Undersampling Technique

In many data mining applications the imbalanced learning problem is becoming ubiquitous nowadays. When the data sets have an unequal distribution of samples among classes, then these data sets are known as imbalanced data sets. When such highly imbalanced data sets are given to any classifier, then classifier may misclassify the rare samples from the minority class. To deal with such type of imbalance, several undersampling as well as oversampling methods were proposed. Many undersampling techniques do not consider distribution of information among the classes, similarly some oversampling techniques lead to the overfitting or may cause overgeneralization problem. This paper proposes an MLPbased undersampling technique (MLPUS) which will preserve the distribution of information while doing undersampling. This technique uses stochastic measure evaluation for identifying important samples from the majority as well as minority samples. Experiments are performed on 5 real world data sets for the evaluation of performance of proposed work. General Terms Machine Learning, Classification.
SILYBUM MARIANUM IN VITRO FLAVONOLIGNAN PRODUCTION

The effect of coniferyl alcohol as a precursor of flavonolignan biosynthesis on silymarin components production in Silybum marianum suspension culture was studied. Coniferyl alcohol showed the changes in silymarin complex production. Silydianin was detected mainly in the control samples of cultivated cells. A significant increase of silydianin was observed only after 72 h of the application of 46μM coniferyl alcohol. No other components of the silymarin complex (silychristin and silybin) were detected; neither in control samples nor after the precursor feeding. But the increased accumulation of taxifolin (flavanole) was very interesting. The highest taxifolin production was reached after 48 hours of treatment (about 554% compared to control).
Simple control rules in a cooperative system for dynamic optimisation problems

The use of centralised, multi-threads cooperative systems, has emerged as a successful alternative to deal with static optimisation problems, avoiding the problem of selecting a particular, isolated strategy. However, when the problem to deal with becomes dynamic in some sense, the question as to whether those systems and the type of control rules employed to control the threads are useful or not remains open. In this article, we depart from a strategy that joint uses a set of solutions and a set of simple agents, and we propose, compare and test two control rules for updating the former. The rules are a simple replacement frequency mechanism and a fuzzy set based one. Computational experiments are performed on the moving peaks benchmark problem under different scenarios and the main conclusions are: first, the fuzzy set based rule is better than the frequency based rule and second, both rules are competitive when compared with a state-of-the-art algorithm.
Proteomic analysis of increased Parkin expression and its interactants provides evidence for a role in modulation of mitochondrial function

Parkin is an ubiquitin‐protein ligase (E3), mutations of which cause juvenile onset – autosomal recessive Parkinson's disease, and result in reduced enzymic activity. In contrast, increased levels are protective against mitochondrial dysfunction and neurodegeneration, the mechanism of which is largely unknown. In this study, 2‐DE and MS proteomic techniques were utilised to investigate the effects of increased Parkin levels on protein expression in whole cell lysates using in an inducible Parkin expression system in HEK293 cells, and also to isolate potential interactants of Parkin using tandem affinity purification and MS. Nine proteins were significantly differentially expressed (±2‐fold change; p<0.05) using 2‐DE analysis. MS revealed the identity of these proteins to be ACAT2, HNRNPK, HSPD1, PGK1, PRDX6, VCL, VIM, TPI1, and IMPDH2. The first seven of these were reduced in expression. Western blot analysis confirmed the reduction in one of these proteins (HNRNPK), and that its levels were dependent on 26S proteasomal activity. Tandem affinity purification/MS revealed 14 potential interactants of Parkin; CKB, DBT, HSPD1, HSPA9, LRPPRC, NDUFS2, PRDX6, SLC25A5, TPI1, UCHL1, UQCRC1, VCL, YWHAZ, YWHAE. Nine of these are directly involved in mitochondrial energy metabolism and glycolysis; four were also identified in the 2‐DE study (HSP60, PRDX6, TPI1, and VCL). This study provides further evidence for a role for Parkin in regulating mitochondrial activity within cells.
Dynamic Orthogonal Range Searching on the RAM, Revisited

© Timothy M. Chan and Konstantinos Tsakalidis. We study a longstanding problem in computational geometry: 2-d dynamic orthogonal range reporting. We present a new data structure achieving O(log n/log log n+k) optimal query time and O(log2/3+o(1)n) update time (amortized) in the word RAM model, where n is the number of data points and k is the output size. This is the first improvement in over 10 years of Mortensen's previous result [SIAM J. Comput. , 2006], which has O (log7/8/ϵn) update time for an arbitrarily small constant ϵ. In the case of 3-sided queries, our update time reduces to O (log1/2+ϵn), improving Wilkinson's previous bound [ESA 2014] of O(log2/3+ϵ).
Cloud Computing Adoption Issues and Applications in Developing Countries: A Qualitative Approach

Cloud computing is an innovative computing reform that provides computing services without any physical boundaries. The purpose of this study is to present the theoretical understanding about cloud benefits, to explore the applications and issues related to cloud computing in IT and Telecom companies of developing countries. Technology- organisation-environment (TOE) framework is used to present the various technological, organisational and environmental factors to adopt the cloud computing. Qualitative research approach is used to analyse this exploratory phenomenon. Firstly, structured interviews were conducted and recorded with an audio device. Subsequently these interviews were transcribed and classified into nodes with the help of NVIVO software and quotations of the interviewees were used for developing relevant themes of study. Various technological, organisational and environmental factors are identified through qualitative data gathering and presented in the context of TOE framework. This study is helpful for the organizations to understand the critical factors essential for implementing a successful cloud environment.
Nonlinear Vibration of Fluid-loaded Double-walled Carbon Nanotubes Subjected To A Moving Load Based on Stochastic FEM

This paper adopts stochastic FEM to study the statistical dynamic behaviors of nonlinear vibration of the fluid-conveying double-walled carbon nanotubes (DWCNTs) under a moving load by considering the effects of the geometric nonlinearity and the nonlinearity of van der Waals (vdW) force. The Young’s modulus of elasticity of the DWCNTs is considered as stochastic with respect to the position to actually characterize the random material properties of the DWCNTs. Besides, the small scale effects of the nonlinear vibration of the DWCNTs are studied by using the theory of nonlocal elasticity. Based on the Hamilton’s principle, the nonlinear governing equations of the fluidconveying double-walled carbon nanotubes under a moving load are formulated. The stochastic finite element method along with the perturbation technique is adopted to study the statistical dynamic response of the DWCNTs. Some statistical dynamic response of the DWCNTs such as the mean values and standard deviations of the non-dimensional dynamic deflections are computed and checked by the Monte Carlo Simulation, meanwhile the effects of the nonlocal parameter and aspect ratio on the statistical dynamic response of the DWCNTs are investigated. It can be concluded that the nonlocal solutions of the dynamic deflections get larger with the increase of the nonlocal parameters due to the small scale effect, and as the aspect ratio increases, the small scale effect has less effect on the maxima non-dimensional dynamic deflections of the DWCNTs.
Optimizing the Treatment of Acute Duct-Destructive Pancreatitis.

The search for new methods for treating duct-destructive pancreatitis is a relevant problem. Endogenous intoxication and oxidative stress that accompany acute pancreatitis often progress even after surgery, which forces one to search for additional possibilities of preventing these severe consequences. This research studied the effect of small doses of direct electric current and intravenous ozone therapy in combination with therapeutic omental pancreatic bursoscopy in the treatment and prevention of the infection of necrotic foci of the pancreas. The rate of postoperative complications in patients with infected pancreatic necrosis and the causes of death of patients with infected pancreatic necrosis were studied.
A Publication of the Association of Management SHAPING ASYMMETRIC SUPPLY CHAIN PARTNERSHIPS : THE ROLE OF SHARED IT AND TRUST

Every organization attempts to minimize transaction costs. One way to do so is by forming partnerships. This paper presents a process view of how shared IT and trust affect transaction costs in a transaction dyad consisting of a small supplier and a large customer. The paper presents a dual perspective of influencing elements; shared IT represents the technological aspects of changes in transaction costs and the Trust represents the human aspects. The base model emphasizes the impact on transaction costs by shared IT and trust. Trust was shown to be the strongest determinant of the reduction in transaction costs; Shared IT demonstrated that it too could reduce transaction costs, but with less influence than trust. The mediating effects of trust are significant on the relationship between shared IT and transaction costs. However, shared IT does have a direct impact on transaction costs and is an important consideration in decisions regarding transaction costs between trading partners of unequal size.
Exploration of vowel onset and offset points for hybrid speech segmentation

Automatic segmentation of speech using embedded reestimation of monophone hidden Markov models (HMMs) followed by forced alignment may not give accurate boundaries. Group delay (GD) processing for refining the boundaries at the syllable level is attempted earlier. This paper aims at exploring vowel onset point (VOP) and vowel offset or end point (VEP) for correcting the boundaries obtained using HMM alignment. HMM models the class information well, however may not detect the exact boundary. In case of VOPs and VEPs, spurious rate or miss rate can be there, but detected boundaries are more accurate. Combining both HMM and VOP/VEP gives improvement in terms of log likelihood scores of forced aligned phoneme boundaries. HMM boundaries are corrected using VOP/VEP and model parameters are reestimated at the syllable level. Results are compared with that of GD based correction and found that overall performance is comparable. Performance for vowels is found to be higher than that of GD based refinement as the refinement in this case is mainly at the vowel boundaries. HMM based speech synthesis systems (HTS) are developed using phone as a basic unit with the proposed segmentation method. Subjective evaluation indicates that there is an improvement in the quality of synthesis.
A framework on automated ventricular analysis of CMR images

Magnetic resonance imaging is a highly advanced reference imaging modality for cardiac morphology, function and perfusion in humans. A framework is proposed for automatic ventricular analysis using cardiac magnetic resonance images. The short axis cine CMR images are corrected for intensity-inhomogeneity using Bias Corrected Fuzzy C-Means method. Ventricular Segmentation of CMR images is important to quantitatively analyze global and regional cardiac function. Extraction of morphological and functional features of CMR images helps in diagnosis of various cardiovascular diseases. The effectiveness of the proposed framework is verified by the experimental results on real CMR images.
Iris Recognition Based on Local Binary Descriptors

The use of biological properties for individual identification, called biometric systems, on mobile devices is the easier and safer approach to deal with user personal information. Several works have been sought to develop robust solutions for different biometric modalities, such as, face, fingerprint, palmprint, voice, and iris recognition. In this work, we evaluate different local binary descriptors, which have fast processing and still efficient memory usage for iris recognition task. At the best of our knowledge, this is the first system that uses local binary descriptors for this task. In our experiments, we compare three wellknown local binary descriptors - BRIEF, ORB and BRISK - in a criterious experimental analysis that considers effectiveness, time-consuming, and memory usage metrics.
Routing approaches and performance evaluation in delay tolerant networks

In this paper the problem of routing in Delay Tolerant Networks (DTNs) is considered. In these networks, where nodes are sparse and the links between them are intermittent, there is no guarantee that a path between source and destination nodes exists at any time, rendering traditional routing protocols unsuitable to deliver messages between nodes. Different DTN routing protocols for stochastic or dynamic networks, where the time-evolving topology is random and not known, are examined. These protocols depend on decisions regarding where and when to forward messages. Performance metrics such as message delivery ratio, average latency, buffer occupancy and average hop count are analyzed in order to compare Direct Delivery, First Contact, epidemic routing and the VACCINE recovery mechanism, Spray and Wait protocols, PROPHET and MaxProp. Simulations show that MaxProp and epidemic protocol combined with VACCINE are able to deliver more messages than the other protocols, ensuring also a lower delivery latency and a lower percentage of buffer occupancy.