LLukas22/scidocs huggingface dataset:
Piloting and validation of a novel self-administered online cognitive screening tool in normal older persons: the Cognitive Function Test.

BACKGROUND
Subtle cognitive changes have been described that may predate the onset of clinically recognizable Alzheimer's disease (AD) and may reflect pathological changes in the brain that are detectable up to 10 years before the onset of AD. Early screening for cognitive status can have benefits in terms of early management and prevention strategies for cognitive decline.


METHOD
A novel computerized cognitive screening tool, the Cognitive Function Test (CFT), was compared with established paper tests of episodic memory, executive function and processing speed, domains previously shown to be predictive of AD, with 50 normal participants, Mini Mental State Examination ≥24, mean age 58.1, SD 5.6 years (range 50-65). An online version, self-administered by 195 eligible respondents without significant memory complaints or dementia, was assessed.


RESULTS
Significant correlations (r = 0.75, p < 0.0001) were found between the CFT and paper tests in a pilot study, showing concurrent validity. The pilot computerized tests were compared with the online version, and no differences were found in mean scores on the total test and domain-specific scores using an algorithm derived from the pilot CFT scores, thus showing internal consistency and reliability of the online format. Norms and 1.5 SD cut-offs for the CFT are presented.


CONCLUSION
The online CFT was shown to be suitable for self-administration in online format (with a mouse response mode) for this midlife age group. Individuals may wish to monitor their cognitive performance before memory concerns are sufficient to warrant visiting a GP or memory clinic.
Transient modeling of ferroelectric capacitors for nonvolatile memories

Present ferroelectric (FE) capacitor models mostly rely on continuous hysteresis loop characteristics of FE materials. Our experimental results show that this approach overestimates the remanent and saturation polarizations available for nonvolatile semiconductor memories by more than 50%. A behavioral transient model based on pulse measurement results is proposed and implemented as an HSPICE macro-model. The model mainly consists of two nonlinear capacitors, corresponding to the two different polarization states of an FE capacitor.
Childhood sun exposure influences risk of multiple sclerosis in monozygotic twins.

OBJECTIVE
To address the role of childhood sun exposure on the risk of multiple sclerosis (MS) after controlling for genetic susceptibility, we investigated the association between sun exposure and MS comparing disease-discordant monozygotic (MZ) twins.


METHOD
Twins with MS were sought by yearly newspaper advertisements throughout North America from 1980 to 1992. Diagnosis was verified by updated medical documentation through 2005. This analysis was restricted to 79 disease- and exposure-discordant monozygotic twin pairs who had ranked themselves before 1993 in relation to each of nine childhood sun exposure activities. A sun exposure index (SI) was defined as the sum of those exposures for which one twin ranked higher than his or her co-twin. The SI difference within each twin pair was calculated by subtracting the SI value of the affected twin from the SI value of the unaffected twin (range -9 to +9). The results were then analyzed using conditional logistic models.


RESULT
Each of the nine sun exposure-related activities during childhood seemed to convey a strong protection against MS within MZ twin pairs. Depending on the activity, the odds ratio (OR) ranged from 0.25 to 0.57. For example, the risk of subsequent MS was substantially lower (OR 0.40, 95% CI 0.19 to 0.83) for the twin who spent more time suntanning in comparison with the co-twin. For each unit increase in SI, the relative risk of MS decreased by 25%.


CONCLUSION
Early sun avoidance seems to precede the diagnosis of multiple sclerosis (MS). This protective effect is independent of genetic susceptibility to MS.
Prevalence and risk factors for depression in a rural setting

Background: Depressive disorders are common, and result in high individual and societal costs. The majority of research assessing depression has occurred in urban areas. There is a paucity of research examining the prevalence of and risk factors for depression in rural general practice. Aim: The aim of this study was to examine the prevalence of and risk factors for depression in a rural area of North Wales in the context of a large multi-centre European study. Method: One thousand nine hundred and ninety-nine people randomly selected from a health authority database underwent a two-phase screening method to identify depression. The first phase involved patients completing a self-rating postal questionnaire (the Beck Depression Inventory or BDI). In the second phase, those scoring above cut-off underwent detailed diagnostic interview (Schedules of Clinical Assessment in Neuropsychiatry or SCAN). The SCAN diagnostic interview can generate either DSM-IV or ICD-10 diagnoses; the DSM-IV classification system was used here. Results: One thousand two hundred and thirty-nine (63 %) people responded to the initial screening questionnaire. The prevalence rate for all DSM-IV depressive disorders was calculated to be 6.1 % (95 % CI 4.1, 9.0) whereas the prevalence rate for DSM-IV major depressive disorder was 5.1 % (CI 3.37, 7.66). Multivariate analysis indicated that several variables were related to BDI caseness, including gender, employment status, social support and negative life events. Conclusion: Levels of reported depression are relatively low in North Wales compared to those observed in a neighbouring urban area using comparable data collection methods. A number of factors traditionally associated with increased risk from depression were predictive of scoring above cut-off on the BDI in a rural North Wales sample.
Process integration of a 27nm, 16Gb Cu ReRAM

A 27nm 16Gb Cu based NV Re-RAM chip has been demonstrated. Novel process introduction to enable this technology include a Damascene Cell, Line-SAC Digit Lines filled with Cu, exhumed-silicided array contacts, raised epitaxial arrays, and high-drive buried access devices.
Effects of Heat Treatments on the Antioxidant Activities of Fruits and Vegetables

The effects of heat treatments on the antioxidant activities of selected fruits and vegetables were investigated by heating at various temperatures (110, 120, 130, 140, and 150C) for 2 hr. The examined fruits and vegetables included tomatoes (Lycopersicon esculentum), oriental melon (Cucumis melon var. makuwa), apples (Malus pumila Miller var. domestica Schneider), melon (Cucumis melon), watermelon (Citrullus vulgaris), and banana (Musa sapientum). The total polyphenol and total flavonoid contents of the juices from heated samples were quantified spectrophotometrically, and their antioxidant activities were determined using DPPH and ABTS radicals. As the heating temperature increased, antioxidant activity also increased. The highest total polyphenol content (2.80 mg/g) occurred in the oriental melon with heating at 150C, and this value was 7 times higher than that of the untreated oriental melon (0.40 mg/g). The highest total flavonoid content (148.80 μg/g) occurred in the melon heat treated at 150C, and this value was 37 times higher than that of the untreated melon (4.54 μg/g). DPPH radical-scavenging activity was the highest in the watermelon treated at 150C (84.37%, 0.50 mg/g), and this value was 40 times higher than that of the untreated watermelon. Finally, the highest ascorbic acid (AA) equivalent antioxidant capacity (AEAC) value (239.50 mg AA eq/g) was obtained in the watermelon heat treated at 150C for 2 hr (control = 18.35 mg AA eq/g).
Large-Scale System Problems Detection by Mining Console Logs

Surprisingly, console logs rarely help operators detect problems in large-scale datacenter services, for they often consist of the voluminous intermixing of messages from many software components written by independent developers. We propose a general methodology to mine this rich source of information to automatically detect system runtime problems. We first parse console logs by combining source code analysis with information retrieval to create composite features. We then analyze these features using machine learning to detect operational problems. We show that our method enables analyses that are impossible with previous methods because of its superior ability to create sophisticated features. We also show how to distill the results of our analysis to an operator-friendly one-page decision tree showing the critical messages associated with the detected problems. We validate our approach using the Darkstar online game server and the Hadoop File System, where we detect numerous real problems with high accuracy and few false positives. In the Hadoop case, we are able to analyze 24 million lines of console logs in 3 minutes. Our methodology works on textual console logs of any size and requires no changes to the service software, no human input, and no knowledge of the software’s internals.
Assessment for frailty is useful for predicting morbidity in elderly patients undergoing colorectal cancer resection whose comorbidities are already optimized.

BACKGROUND
The clinical syndrome of frailty identified through the assessment of weight loss, gait speed, grip strength, physical activity, and physical exhaustion has been used to identify patients with reduced reserves. We hypothesized that frailty is useful in predicting adverse outcomes in optimized elective elderly colorectal surgery patients.


METHODS
A prospective study was conducted at 2 centers (Singapore and Japan). All patients over 75 years of age undergoing colorectal resection were assessed for the presence of the syndrome of frailty. All these patients had already had their comorbidities optimized for surgery. The outcome measure was postoperative major complications (defined as Clavien-Dindo type II and above complications).


RESULTS
Eighty-three patients were studied from February 2008 to April 2010. The mean age was 81.5 years (range 75-93 years). The mean comorbidity index was 3.37 (range 0-11). Twenty-six (31.3%) patients were an American Society of Anesthesiologists (ASA) score of 3 and above. Chi-square analysis revealed that the odds ratio of postoperative major complications was 4.083 (95% confidence interval, 1.433-11.638) when the patient satisfied the criteria for frailty. Albumin <35, ASA >3, comorbidity index >5, and Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) scores were not predictive of postoperative major complications.


CONCLUSIONS
Preliminary findings show that frailty is a potent adjunctive tool of predicting postoperative morbidity. Frailty can be used to identify elderly patients needing further optimization before major surgery.
Complexity leadership in bureaucratic forms of organizing : A meso model

We consider Complexity Leadership Theory [Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity Leadership Theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly.] in contexts of bureaucratic forms of organizing to describe how adaptive dynamics can work in combination with administrative functions to generate emergence and change in organizations. Complexity leadership approaches are consistent with the central assertion of the meso argument that leadership is multi-level, processual, contextual, and interactive. In this paper we focus on the adaptive function, an interactive process between adaptive leadership (an agentic behavior) and complexity dynamics (nonagentic social dynamics) that generates emergent outcomes (e.g., innovation, learning, adaptability) for the firm. Propositions regarding the actions of complexity leadership in bureaucratic forms of organizing are offered. © 2009 Elsevier Inc. All rights reserved.
The evolution of innovation management towards contextual innovation

Purpose – In recent decades, innovation management has changed. This article provides an overview of the changes that have taken place, focusing on innovation management in large companies, with the aim of explaining that innovation management has evolved toward a contextual approach, which it will explain and illustrate using two cases. Design/methodology/approach – The basic approach in this article is to juxtapose a review of existing literature regarding trends in innovation management and research and development (R&D) management generations, and empirical data about actual approaches to innovation. Findings – The idea that there is a single mainstream innovation approach does not match with the (successful) approaches companies have adopted. What is required is a contextual approach. However, research with regard to such an approach is fragmented. Decisions to adapt the innovation management approach to the newness of an innovation or the type of organization respectively have thus far been investigated separately. Research limitations/implications – An integrated approach is needed to support the intuitive decisions managers make to tailor their innovation approach to the type of innovation, organization(s), industry and country/culture. Originality/value – The practical and scientific value of this paper is that is describes an integrated approach to contextual innovation.
Some New Parallel Fast Fourier Transform Algorithms

Discrete Fourier transform (DFT) has many applications in digital signal and image processing and other scientific and technological domains, but its time complexity of direct computation is O(n2), limiting greatly its application range. Thus many people have developed fast Fourier transform (FFT) algorithms, reducing the complexity from O(n2) to O(nlogn)(In this paper logn denotes log2n).But for large n, O(nlogn) is still very high. So multiprocessor systems have been used to speed up the computation of DFT. This paper first introduces a new general method to deduce FFT algorithms, then transforms the deduced second radix-2 decimation-in-time FFT algorithm into another parallelizable sequential form, and finally transforms the latter algorithm into a new parallel FFT algorithm, reducing the time complexity of DFT to O(nlogn/p) (where p is the number of processors). Using similar methods, the authors can also design other new parallel 1-D and 2-D FFT algorithms.
The outcome of scaphoid excision and four-corner arthrodesis for advanced carpal collapse at a minimum of ten years.

PURPOSE
Scaphoid excision and 4-corner arthrodesis is a salvage option for patients with advanced carpal collapse. This study aims to compare the clinical outcomes of 4-corner arthrodesis (FCA) at one year, 2 years, and a minimum of 10 years.


METHODS
A cohort study was performed of patients having scaphoid excision and FCA procedure by a single surgeon. Thirty-one of 35 recruited were followed up for 10 years. The mean patient age was 47 years. All patients had scaphoid excision and FCA, using bone graft and 3M Shapiro staples (3M, St Paul, MN). Patients were followed up prospectively at one year, 2 years, and a minimum of 10 years after surgery by an independent observer. Three patients were lost to follow-up between the 2-year and 10-year assessments because they were untraceable, and one patient died at 7 years, without any further intervention. Before surgery, pain scores measured with a visual analog scale, range of wrist movement, grip and pinch strength, and scores from a self-assessment functional questionnaire were recorded prospectively. These measures were repeated at each time point, in addition to patient satisfaction scores measured on a visual analog scale.


RESULTS
The pain scores decreased from a median preoperative score of 6/10 to 0/10 at one year. Grip strength did not change significantly. Wrist flexion decreased significantly after surgery, by an average of 22%. The average patient-reported satisfaction score was 8/10. There was no significant change in pain, wrist function, satisfaction, or arc of motion between one and 10 years. Two of 35 patients recruited had gone on to a total wrist arthrodesis for ongoing pain.


CONCLUSIONS
The outcome of scaphoid excision and 4-corner arthrodesis is favorable at one year and does not deteriorate significantly between one and 10 years. There is a low rate of conversion to total wrist arthrodesis. Pain scores are reduced at the cost of reduced wrist flexion.
Dynamic Graph CNN for Learning on Point Clouds

Point clouds provide a flexible and scalable geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices. Hence, the design of intelligent computational models that act directly on point clouds is critical, especially when efficiency considerations or noise preclude the possibility of expensive denoising and meshing procedures. While hand-designed features on point clouds have long been proposed in graphics and vision, however, the recent overwhelming success of convolutional neural networks (CNNs) for image analysis suggests the value of adapting insight from CNN to the point cloud world. To this end, we propose a new neural network module dubbed EdgeConv suitable for CNN-based high-level tasks on point clouds including classification and segmentation. EdgeConv is differentiable and can be plugged into existing architectures. Compared to existing modules operating largely in extrinsic space or treating each point independently, EdgeConv has several appealing properties: It incorporates local neighborhood information; it can be stacked or recurrently applied to learn global shape properties; and in multi-layer systems affinity in feature space captures semantic characteristics over potentially long distances in the original embedding. Beyond proposing this module, we provide extensive evaluation and analysis revealing that EdgeConv captures and exploits fine-grained geometric properties of point clouds. The proposed approach achieves state-of-the-art performance on standard benchmarks including ModelNet40 and S3DIS. ∗Equal Contribution
Financial Sustainability of Microfinance Institutions (MFIs) in Ethiopia

The microfinance paradigms focus on reduction of poverty through improving access to finance and financial services. However, the positive impacts of microfinance institutions on the welfare of the poor can only be sustained if the institutions can achieve a good financial performance. The purpose of this study, therefore, aimed at identifying factors affecting financial sustainability of MFIs in Ethiopia. The study followed a quantitative research approach using a balanced panel data set of 126 observations from 14 MFIs over the period 2002-2010. The study found that microfinance breadth of outreach, depth of outreach, dependency ratio and cost per borrower affect the financial sustainability of microfinance institutions in Ethiopia. However, the microfinance capital structure and staff productivity have insignificant impact on financial sustainability of MFIs in Ethiopia for the study periods.
Phase I study of cisdiamminedichloroplatinum in combination with azidothymidine in the treatment of patients with advanced malignancies

 Purpose. Azidothymidine (AZT, zidovudine) has been shown to reverse cisplatin resistance in cell culture. This phase I study was performed to determine the maximally tolerated dose (MTD) and dose-limiting toxicities of AZT when administered by continuous intravenous infusion in combination with cisplatin (CDDP), and to evaluate the pharmacokinetics of AZT in this setting. Patients and methods. Entered in the study were 61 patients with advanced, histologically confirmed malignancies which were unresponsive to or for which no "standard" chemotherapeutic regimen existed. AZT was administered as a 72-h infusion on days 1–3 and 14–16 of a 28-day cycle at dose levels from 400 through 14,364 mg/m2 per day. CDDP at dose levels of 30, 45, or 60 mg/m2 was administered at hour 36 of each AZT infusion. The plasma pharmacokinetics of AZT were determined in patients treated at representative dose levels. Results. Of the 61 patients who completed 125 courses of therapy, 21 had stable disease for a median of four cycles (range two to eight), 33 progressed on therapy, and 7 were not assessable for response. The major observed toxicity was myelosuppression. The MTD of AZT was 8135 mg/m2 per day when administered on this schedule. Escalation of CDDP did not result in additive toxicity. The mean steady-state level of AZT at the MTD was 44 μM (range 35–51 μM). Conclusions. Steady-state concentrations of AZT increased with dose. The plasma levels achieved at the MTD exceeded those required for drug resistance reversal in vitro. The administration of CDDP had no effect on AZT steady-state levels. The dose-limiting toxicity of this drug combination is myelosuppression. AZT may be useful in further studies utilizing combination therapy to achieve increased chemotherapy effectiveness.
Principles of parametric temporal imaging. I. System configurations

The recently developed process of temporal imaging expands or compresses time waveforms while preserving the shapes of their envelope profiles. A key element in a temporal imaging system is a time lens which imparts a quadratic phase modulation to the waveform being imaged. Several methods, such as electrooptic modulation, can be used to produce the phase modulation. In this paper, we concentrate on the parametric mixing of a signal waveform with a linearly chirped optical pump as the time lens mechanism. We analyze all single-lens system configurations including sum- and difference-frequency mixing schemes with positive and negative group velocity dispersions using temporal ray diagrams as an aid in understanding their operation.
A System for Interactive Visual Analysis of Large Graphs Using Motifs in Graph Editing and Aggregation

Network analysis is an important task in a wide variety of application domains including analysis of social, financial, or transportation networks, to name a few. The appropriate visualization of graphs may reveal useful insight into relationships between network entities and subnetworks. However, often further algorithmic analysis of network structures is needed. In this paper, we propose a system for effective visual analysis of graphs which supports multiple analytic tasks. Our system enhances any graph layout algorithm by an analysis stage which detects predefined or arbitrarily specified subgraph structures (motifs). These motifs in turn are used to filter or aggregate the given network, which is particularly useful for search and analysis of interesting structures in large graphs. Our approach is fully interactive and can be iteratively refined, supporting analysis of graph structures at multiple levels of abstraction. Furthermore, our system supports the analysis of dataor user-driven graph dynamics by showing the implications of graph changes on the identified subgraph structures. The interactive facilities may be flexibly combined for gaining deep insight into the network structures for a wide range of analysis tasks. While we focus on directed, weighted graphs, the proposed tools can be easily extended to undirected and unweighted graphs. The usefulness of our approach is demonstrated by application on a phone call data set [18].