LLukas22/scidocs huggingface dataset:
Patterns of early change and their relationship to outcome and follow-up among patients with major depressive disorders.

BACKGROUND
While highlighting the efficacy of different treatments for major depressive disorders (MDD), findings of the National Institute of Mental Health (NIMH) Treatment of Depression Collaborative Research Program (TDCRP) often are interpreted as supporting the idea of treatment non-specificity for MDD. However, heterogeneity in treatment courses and outcomes might be undetected when focusing only on types of treatment in terms of sample means without taking into account early change in treatment.


METHOD
In this study, growth mixture models (GMM) were used in the completer sample of N=162 patients from the NIMH TDCRP to identify meaningful patterns of early change of depression severity that are shared by many individual patients.


RESULTS
Results revealed three typical patterns of early change over the first 8 weeks of treatment irrespective of the type of treatment protocol provided: (a) moderate to severe depression with moderate early improvement, (b) moderate to severe depression with rapid early improvement, and (c) mild to moderate depression with moderate early improvement. In contrast to the type of treatment, these differential patterns of early response (together with overall pre-treatment symptom severity) predicted outcomes (i.e. depression severity) at treatment termination and over the 1.5-year follow-up period.


LIMITATIONS
Due to the small sample size and the controlled setting of this study the degree to which these results can be generalized to clinical practice has to be further investigated.


CONCLUSIONS
The findings provide further support for the assumption that early change is an important factor for the prediction of short- and long-term outcome in psychotherapy.
A Bidirectional Modular Multilevel DC–DC Converter of Triangular Structure

In this paper, a novel bidirectional modular multilevel dc-dc converter is proposed. The proposed topology, named the triangular modular multilevel dc-dc converter (TMMC), can achieve equal power sharing among its modules over a broad range of conversion ratios. The proposed control algorithm provides localized control of modules which enhances the converter's dynamic performance and design flexibility. A 1.7-kW experimental implementation of the converter is shown to achieve an efficiency of 95.9% and 96.2% in step-up and step-down modes, respectively. Significant reductions in the input current and output voltage ripples are observed through the interleaved operation of the converter. The TMMC also provides multiple fixed voltage nodes which makes it suitable as a multiple-input multiple-output converter.
The impact of high-frequency repetitive transcranial magnetic stimulation on fine motor functions in medication-resistant major depression.

OBJECTIVES
Although high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) over the left dorsolateral prefrontal cortex (DLPFC) has been reported to improve mood symptoms in major depressive disorder (MDD), research on its impact on psychomotor symptoms is scarce. This study assessed the psychomotor effects of 1 and 10 sessions, respectively, of HF-rTMS over the left DLPFC.


METHODS
Ten HF-rTMS sessions were applied in 21 medication-free MDD patients over a 2-week period. At the beginning, one placebo (sham)-controlled rTMS session was also applied in a cross-over, single-blind design. Psychomotor variables were digitally recorded during completion of a Fitts' task, at baseline, after the first and second real/sham session and at the end point.


RESULTS
The total 10-session treatment period resulted in a decrease of depression severity. One HF-rTMS session resulted in improvements on the Fitts' task, without a difference between active and sham stimulation, however. No further improvements occurred from session 2 to session 10.


CONCLUSIONS
No evidence was provided to link the observed psychomotor improvements to HF-rTMS stimulation, as a practice effect could have impacted the significant psychomotor outcomes.
Similar antiviral efficacy and tolerability between efavirenz and lopinavir/ritonavir, administered with abacavir/lamivudine (Kivexa), in antiretroviral-naïve patients: a 48-week, multicentre, randomized study (Lake Study).

BACKGROUND
Although efavirenz and lopinavir/ritonavir(r) are both recommended antiretroviral agents in antiretroviral-naïve HIV-infected patients, there are few randomized comparisons of their efficacy and tolerability.


METHODS
A multicenter and randomized study was performed including 126 antiretroviral-naïve patients, randomly assigned to efavirenz+Kivexa (n=63) or lopinavir/r+Kivexa (n=63). Efficacy endpoints were the percentage of patients with HIV-RNA < or =50 copies/mL at week 48 and CD4 recovery. Safety was assessed by comparing toxicity and discontinuations. Statistical analyses were performed on an intention-to-treat (ITT) basis (Missing=Failure).


RESULTS
At week 48, 56.7% of patients in the efavirenz and 63.2% in the lopinavir/r groups showed HIV-1 RNA <50 copies/mL (P=0.770) (intention-to-treat analysis; Missing=Failure). Only 1 (1.53%) patient from each group experienced virological failure. CD4 values increased in both groups (298 cells in the efavirenz group, P=0.001; 249 cells in the lopinavir/r group, P=0.002; P=0.126 between groups). HDL-cholesterol only increased in the efavirenz group (from 39+/-12 mg/dL to 49+/-11; P=0.001). Discontinuations were more frequent in the lopinavir/r group (36.5% versus 28.5%; P=0.193), but more patients with efavirenz interrupted due to toxicity (11.1% versus 6.3%); most of them were attributed to hypersensitivity reaction.


CONCLUSIONS
Similar virological efficacy was observed for efavirenz and lopinavir/r, when administered with Kivexa in antiretroviral-naïve patients, while immunological improvement was slightly superior for efavirenz. The higher rate of discontinuation due to toxicity in the efavirenz group was related to a higher incidence of hypersensitivity reaction. Nowadays, the use of the new formulation of lopinavir/r and the HLA-B*5701 genotype test before starting abacavir should improve the safety profiles of these regimens.
Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia

Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall forecasting. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multilayer perceptron neural networks (MLP-NN). In fact, the rainfall time series modeling involves an important temporal dimension. On the other hand, the classical MLP-NN is a static and has a memoryless network architecture that is effective for complex nonlinear static mapping. This research focuses on investigating the potential of introducing a neural network that could address the temporal relationships of the rainfall series. Two different static neural networks and one dynamic neural network, namely the multi-layer perceptron neural network (MLP-NN), radial basis function neural network (RBFNN) and input delay neural network (IDNN), respectively, have been examined in this study. Those models had been developed for the two time horizons for monthly and weekly rainfall forecasting at Klang River, Malaysia. Data collected over 12 yr (1997–2008) on a weekly basis and 22 yr (1987–2008) on a monthly basis were used to develop and examine the performance of the proposed models. Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static and dynamic neural networks. Results showed that the MLP-NN neural network model is able to follow trends of the actual rainfall, however, not very accurately. RBFNN model achieved better accuracy than the MLP-NN model. Moreover, the forecasting accuracy of the IDNN model was better than that of static network during both training and testing stages, which proves a consistent level of accuracy with seen and unseen data.
Explaining ERP failure in a developing country: a Jordanian case study

Purpose ­ Enterprise resource planning (ERP) systems are increasingly being adopted by organisations in developing countries. As in industrialised countries, this adoption seems beset by significant rates of failure, leading to a large waste of investment and other resources. This study seeks to understand why such ERP failure occurs. Design/methodology/approach ­ This study moves beyond factor lists to make use of an overall "design—reality gap" model. The model is applied to a case study of ERP failure in a Jordanian manufacturing firm, analysing the situation both before and during ERP implementation through a mix of interviews, observation and document analysis. Findings ­ The research finds sizeable gaps between the assumptions and requirements built into ERP system design, and the actual realities of the client organisation. It is these gaps – and the failure to close them during implementation – that underlie ERP project failure. Research limitations/implications ­ This study shows the relevance and applicability of the design—reality gap model to understanding ERP failure. Further research can be undertaken applying the model to other ERP cases, including case studies of success. Practical implications ­ The paper draws conclusions about good practice in ERP implementation relating to both risk identification and risk mitigation, which must be based on closing design—reality gaps. It offers examples of both specific and generic actions that help to achieve this. But it also notes limitations existing in some developing country contexts that may continue to constrain the effective use of enterprise resource planning systems. 2 Originality/value ­ This study provides a new model for understanding ERP project success and failure, and for practical risk mitigation. The design—reality gap model aims to be comprehensive but also contingent; sensitive to the specific conditions of any individual client organisation.
Heap Data Allocation to Scratch-Pad Memory in Embedded Systems

Title of dissertation: Heap Data Allocation To Scratch-Pad Memory In Embedded Systems Angel Dominguez Doctor of Philosophy, 2007 Dissertation directed by: Professor Rajeev K. Barua Department of Electrical and Computer Engineering This thesis presents the first-ever compile-time method for allocating a portion of a program’s dynamic data to scratch-pad memory. A scratch-pad is a fast directly addressed compiler-managed SRAM memory that replaces the hardware-managed cache. It is motivated by its better real-time guarantees vs cache and by its significantly lower overheads in access time, energy consumption, area and overall runtime. Dynamic data refers to all objects allocated at run-time in a program, as opposed to static data objects which are allocated at compile-time. Existing compiler methods for allocating data to scratch-pad are able to place only code, global and stack data (static data) in scratch-pad memory; heap and recursive-function objects(dynamic data) are allocated entirely in DRAM, resulting in poor performance for these dynamic data types. Runtime methods based on software caching can place data in scratch-pad, but because of their high overheads from software address translation, they have not been successful, especially for dynamic data. In this thesis we present a dynamic yet compiler-directed allocation method for dynamic data that for the first time, (i) is able to place a portion of the dynamic data in scratch-pad; (ii) has no software-caching tags; (iii) requires no run-time peraccess extra address translation; and (iv) is able to move dynamic data back and forth between scratch-pad and DRAM to better track the program’s locality characteristics. With our method, code, global, stack and heap variables can share the same scratch-pad. When compared to placing all dynamic data variables in DRAM and only static data in scratch-pad, our results show that our method reduces the average runtime of our benchmarks by 22.3%, and the average power consumption by 26.7%, for the same size of scratch-pad fixed at 5% of total data size. Significant savings in runtime and energy across a large number of benchmarks were also observed when compared against cache memory organizations, showing our method’s success under constrained SRAM sizes when dealing with dynamic data. Lastly, our method is able to minimize the profile dependence issues which plague all similar allocation methods through careful analysis of static and dynamic profile information. Heap Data Allocation To Scratch-Pad Memory In Embedded Systems
Giovanni Giorgi (1871–1950)

The rare combination of a theoretician and a practical engineer was found in Giovanni Giorgi. His theory of alternating sinusoidal currents and their representation by means of vector diagrams is fundamental to the science of engineering. At the same time he planned and organized many civic engineering projects for the benefit of his people.
Image processing for mango ripening stage detection: RGB and HSV method

Mango is one of the commercial fruits produced and consumed throughout the world. Mangos are needed to be classified according to their ripening stage for commercial use. Currently this classification is being performed manually which is not accurate and prone to human errors. Also it adds up the manpower and thereby overall cost and effectiveness of the mango processing industries. In this paper we have proposed two methods for classification of mangos based on changes in their visual features. We have considered Alphonso mango in our work as it is one of the most famous and traded mango type. But the proposed methods can be applied to any other species of mango which changes color with ripening process. In RGB method, the ripening stage is detected based on the red, green and blue components of the image pixels whereas in HSV method the hue-saturation-value map is analyzed for the detection. Algorithms are proposed and implemented using MATLAB. Results are compared with the manual results and found to be 90.4 and 84.2% accurate in case of RGB and HSV respectively. It is also demonstrated that the proposed methods are insensitive to amount of ambient light, provided that the image is taken in the natural light or under the white light.
Association of epicardial adipose tissue with progression of coronary artery calcification is more pronounced in the early phase of atherosclerosis: results from the Heinz Nixdorf recall study.

OBJECTIVES
This study sought to determine whether epicardial adipose tissue (EAT) volume predicts the progression of coronary artery calcification (CAC) score in the general population.


BACKGROUND
EAT predicts coronary events and is suggested to influence the development of atherosclerosis.


METHODS
We included 3,367 subjects (mean age 59 8 years; 47% male) from the population-based Heinz Nixdorf Recall study without known coronary artery disease at baseline. CAC was quantified from noncontrast cardiac electron beam computed tomography at baseline and after 5 years. EAT was defined as fat volume inside the pericardial sac and was quantified from axial computed tomography images. Association of EAT volume with CAC progression (log[CAC(follow-up) + 1] - log[CAC(baseline) + 1]) was depicted as percent progression of CAC + 1 per SD of EAT.


RESULTS
Subjects with progression of CAC above the median had higher EAT volume than subjects with less CAC change (101.1 ± 47.1 ml vs. 84.4 43.4 ml; p < 0.0001). In regression analysis, 6.3% (95% confidence interval [CI]:2.3% to 10.4%; p = 0.0019) of progression of CAC + 1 was attributable to 1 SD of EAT, which persisted after adjustment for risk factors (6.1% [95% CI: 1.2% to 11.2%]; p ¼ 0.014). For subjects with a CAC score of >0 to ≤100, progression of CAC þ 1 by 20% (95% CI: 11% to 31%; p < 0.0001) was attributable to 1 SD of EAT. Effect sizes decreased with CAC at baseline, with no relevant link for subjects with a CAC score ≤400 (0.2% [95% CI: -3.5% to 4.2%]; p = 0.9). Likewise, subjects age <55 years at baseline showed the strongest association of EAT with CAC progression (20.6% [95% CI: 9.7% to 32.5%]; p < 0.0001). Interestingly, the effect of EAT on CAC progression was more pronounced in subjects with low body mass index (BMI), and decreased with degree of adiposity (BMI ≤25 kg/m(2):19.8% [95% CI: 9.2% to 31.4%]; p = 0.0001, BMI >40 kg/m(2): 0.8% [95% CI: -26.7% to 38.9%]; p = 0.96).


CONCLUSIONS
EAT is associated with the progression of CAC, especially in young subjects and subjects with low CAC score, suggesting that EAT may promote early atherosclerosis development.
Economic order quantity under conditionally permissible delay in payments

Within the economic order quantity (EOQ) framework, the main purpose of this paper is to investigate the retailer’s optimal replenishment policy under permissible delay in payments. All previously published articles dealing with optimal order quantity with permissible delay in payments assumed that the supplier only offers the retailer fully permissible delay in payments if the retailer ordered a sufficient quantity. Otherwise, permissible delay in payments would not be permitted. However, in this paper, we want to extend this extreme case by assuming that the supplier would offer the retailer partially permissible delay in payments when the order quantity is smaller than a predetermined quantity. Under this condition, we model the retailer’s inventory system as a cost minimization problem to determine the retailer’s optimal inventory cycle time and optimal order quantity. Three theorems are established to describe the optimal replenishment policy for the retailer. Some previously published results of other researchers can be deduced as special cases. Finally, numerical examples are given to illustrate all these theorems and to draw managerial insights.
Realtime 4D CAD = RFID for Project Progress Management

This research presents the integration of 4D CAD with RFID (Radio Frequency IDentification) technology to improve the progress management process. The objective of this research was to build an effective and efficient project progress management framework by integrating 4D CAD with RFID technology under a collaborative environment throughout the supply chain of a construction project. This research proposes a system, named 4D+RFID, that presents building elements in 3D CAD models according to as-built progress, where the as-built information is collected in real-time by sensing the progress throughout the supply chain using RFID. 4D+RFID developed in this research aims at supporting processes with a focus on structural and curtain wall elements, such as steel columns and beams, concrete slabs, and curtain walls, which are typically on the critical path of project schedules in high-rise building construction projects. The process is that RFID is applied to sense the progress status of ordering, delivery, receiving, and erection of building elements, and then the as-built progress information is presented in 3D CAD models. 4D+RFID is under development for use in a high-rise office building construction project in downtown Seoul, Korea.
Provenance and tectonic setting of the Carboniferous sedimentary rocks of the East Junggar Basin, China: Evidence from geochemistry and U–Pb zircon geochronology

Abstract The modern Junggar Basin was located in the Central Asian Orogenic Belt (CAOB) during the Devonian and Carboniferous. Few data concerning the weathering, provenance and tectonic setting of the Carboniferous sedimentary rocks in the Junggar Basin have been published. The recent discovery of an oil–gas field in the East Junggar Basin provides the impetus for this study. Twenty-eight sediment samples were recovered from eight boreholes, and all were analysed for major and trace element geochemistry. Two samples of sedimentary rocks were selected for zircon U–Pb dating. Low chemical index of alteration (CIA) values (44–71) and relatively high index of compositional variability (ICV) values (0.72–1.83) suggested weak chemical weathering and an immature source for these samples. The relatively low Th/U (2.16–10.55) and Rb/Sr (0.03–5.44) ratios of the drill core samples reflect a simple recycling history. Two samples indicated upper Carboniferous ages (314.6 Ma) and a lower-middle Devonian age (397.9 Ma). Geochemistry and detrital zircon geochronology from the East Junggar Basin reveal a distinct difference in the composition and source rock ages of clastic rocks from the lower and the upper Carboniferous. Major and trace element compositions of the lower Carboniferous sedimentary rocks (LCRs) were derived from typical mafic rocks and an intermediate ocean island arc of early to middle Devonian age, whereas the upper Carboniferous sedimentary rocks (UCRs) were derived from a continental island arc or active continental margin setting with a dominantly felsic to intermediate late Carboniferous age. The current data provide little support for tectonic models that show a passive continental margin of a Precambrian crystalline basement; our study suggests that a volcanic arc accretion or archipelago (early Carboniferous to early-middle Devonian) model for the East Junggar Basin is more viable.
Mining Students' Academic Performance

Data Mining techniques are widely used in educational field to find new hidden patterns from student’s data. The hidden patterns that are discovered can be used to understand the problem arise in the educational field. This paper surveys the three elements needed to make prediction on Students’ Academic Performances which are parameters, methods and tools. This paper also proposes a framework for predicting the performance of first year bachelor students in computer science course. Naïve Bayes Classifier is used to extract patterns using the Data Mining Weka tool. The framework can be used as a basis for the system implementation and prediction of Students’ Academic Performance in Higher Learning Institutions.
GM Plan: a gate matrix layout algorithm based on artificial intelligence planning techniques

In this paper, the CMOS gate matrix layout problem is formulated and solved as a n artificial intelligence planning problem in which a “plan” (the solution algorithm) is to be generated to achieve a “goal” (the gate matrix layout). The overall goal consists of many subgoals, each of which corresponds to the placement of a gate to a slot, and to the routing of associated nets connecting to that gate. As different nets compete for track (resource) usage, these subgoals interact (interfere) with each other, rendering suboptimal solutions. In this paper, such interaction among subgoals is managed with two artificial intelligence planning techniques: hierarchical subgoal organization and domain independent search control policies. The subgoal hierarchy facilitates an objective classification of the subgoals into priority classes according to a proposed distance measure of connectivity. Two search control policies (general problem solving heuristics)-most-constraint (MC) and least impact (L1)-are used to guide the search process. The MC policy states that the subgoal whose solution has most constraints should be attempted first. The LI policy states that among many alternate solutions, the one that consumes the least amount of resources, and hence, preserves the most flexibility should be chosen. Using these techniques, we developed a planning-based gate matrix layout algorithm, called GM-Plan, which combines the gate placement and net routing into a single, incremental problem solving loop. Encouraging results have been observed in a number of test examples.