Miracle-dz/UniFAR-FTUs huggingface dataset:
Soil Chemical and Microbial Properties in a Mixed Stand of Spruce and Birch in the Ore Mountains (Germany)—A Case Study

A major argument for incorporating deciduous tree species in coniferous forest stands is their role in the amelioration and stabilisation of biogeochemical cycles. Current forest management strategies in central Europe aim to increase the area of mixed stands. In order to formulate statements about the ecological effects of mixtures, studies at the stand level are necessary. In a mixed stand of Norway spruce (Picea abies (L.) Karst. ) and silver birch (Betula pendula Roth) in the Ore Mountains (Saxony, Germany), the effects of these two tree species on chemical and microbial parameters in the topsoil were studied at one site in the form of a case study. Samples were taken from the O layer and A horizon in areas of the stand influenced by either birch, spruce or a mixture of birch and spruce. The microbial biomass, basal respiration, metabolic quotient, pH-value and the C and N contents and stocks were analysed in the horizons Of, Oh and A. Significantly higher contents of microbial N were observed in the Of and Oh horizons in the birch and in the spruce-birch strata than in the stratum containing only spruce. The same was found with respect to pH-values in the Of horizon and basal respiration in the Oh horizon. Compared to the spruce stratum, in the birch and spruce-birch strata, significantly lower values were found for the contents of organic C and total N in the A horizon. The findings of the case study indicated that single birch trees have significant effects on the chemical and microbial topsoil properties in spruce-dominated stands. Therefore, the admixture of birch in spruce stands may distinctly affect nutrient cycling and may also be relevant for soil carbon sequestration. Further studies of these functional aspects are recommended.
Chapter N hpDJ : An automated DJ with floorshow feedback

This report describes extensions to the hpDJ automated dance-music disk-jockey system, that allow it to monitor the responses of a crowd of listeners and react to their changing responses. Although the initial intention was simply to allow the crowd responses to guide the selection of the next pre-recorded music song to play, the nature of the feedback is such that it can be used to help compose new variations on existing tunes, or potentially entirely new music too.
Role of neuropsychological assessment in the differential diagnosis of Alzheimer’s disease and vascular dementia

The prevalence of dementia increases significantly from the age of 65 years, doubling every five years thereafter. Alzheimer’s disease (AD) and vascular dementia (VaD) constitute the two main dementia types. Differentiating them encompasses anamnesis, neurological examination, laboratory and neuroimaging exams and neuropsychological assessment. Neuropsychological assessment produces different findings for each dementia type, and reveals those areas most impaired as well as those most preserved. The aim of the present article was to describe the role of neuropsychology in diagnosing dementia and achieving a differential diagnosis between AD and VaD. A general overview follows of the most widely known instruments used to assess cognitive function in dementia, and the cognitive changes seen in AD and VaD. The conclusion drawn was that there is significant overlap in cognitive changes between both these dementia types, while each type has its own specific characteristics which are identifiable and quantifiable on neuropsychological assessments and provide the basis for reaching a differential diagnosis.
Task-oriented work characteristics, self-efficacy, and service-oriented organizational citizenship behavior: A cross-level analysis of the moderating effect of social work characteristics and collective efficacy

Purpose Border management, barring illegal foreign workers, and immigrant counseling are three major functions of the National Immigration Agency (NIA) of Taiwan. These functions are composed of traditional “job” as well as social “work” characteristics. In other words, these functions have shifted from a “position”-based job design to an “overall operation”-based work design that incorporates environmental and situational factors. The purpose of this paper is to examine frontline immigration workers in Taiwan in order to determine how the motivational (task-oriented) and social work (social-oriented) characteristics (SWCs) of the immigration work design model influence immigration workers’ organizational citizenship behaviors (OCBs). Design/methodology/approach The authors collected 312 questionnaires, of which 304 were valid, with 230 completed by men and 74 by women. Findings The results revealed that SWCs and collective efficacy at the group level had significantly positive effects on collective efficacy and service-oriented OCB, respectively. Task-oriented work characteristics had positive effects on self-efficacy and thus on individual level service-oriented OCB, and self-efficacy also had positive effects on individual service-oriented OCB. Both SWCs and collective efficacy had a contextual effect on individual-level outcome variables. Furthermore, the combination of SWCs with self-efficacy had cross-level effects on individuals’ service-oriented OCB. Originality/value These findings can enhance people’s understanding of how the social and motivational power of work characteristics can encourage employees to exhibit service-oriented OCB. This implies that the NIA can stimulate individual self-motivation and affect group-level efficacy and service-oriented OCB through the environmental context and social relationship characteristics of border affairs brigades (branches).
A Method of Accounting Bigrams in Topic Models

The paper describes the results of an empirical study of integrating bigram collocations and similarities between them and unigrams into topic models. First of all, we propose a novel algorithm PLSA-SIM that is a modification of the original algorithm PLSA. It incorporates bigrams and maintains relationships between unigrams and bigrams based on their component structure. Then we analyze a variety of word association measures in order to integrate top-ranked bigrams into topic models. All experiments were conducted on four text collections of different domains and languages. The experiments distinguish a subgroup of tested measures that produce topranked bigrams, which demonstrate significant improvement of topic models quality for all collections, when integrated into PLSASIM algorithm.
A quantitative study of Idaho high school seniors' postsecondary decision-making influences

The purpose of this study is to assist state, district, and high school educational leadership in understanding the influences of the Idaho high school students’ postsecondary decision-making. The literature review established five categories that influence students’ postsecondary decisionmaking: postsecondary and career awareness, postsecondary and career admissions process, academic readiness for postsecondary education and careers, postsecondary monetary cost, and social capital influence for postsecondary education. The theoretical framework for the study was the work of Perna’s proposed conceptual model of students’ college choice. Descriptive quantitative research methods were used to survey 566 high school seniors from south western Idaho during their fall 2014 semester. Participants selected social capital influence for postsecondary education as the greatest influence on their college decision-making. Correlations were run to find if any relationship existed between students’ postsecondary plans and income, counseling services, and parental educational level. All three categories demonstrated statistical significance, however, none achieved practical significance. Participant responses pertaining to counseling services indicated that many students were not satisfied or were unsure about the services their school counselor provided.
A schema matching-based approach to XML schema clustering

The relationship between XML data clustering and schema matching is bidirectional. On one side, clustering techniques have been adopted to improve matching performance, and on the other side schema matching is the backbone of the clustering technique. This paper presents a new approach for clustering XML schema based on schema matching. In particular, we develop and implement an XML schema matching system, which determines semantic similarities between XML schemas based on the Prüfer sequence representation of schema trees. The proposed computation similarity algorithm makes use of the semantic meaning of XML elements as well as the hierarchical features of XML schemas. The computed similarities are then exploited by an agglomerative clustering algorithm to group similar schemas. Our experimental results show that the proposed approach is fast and accurate in clustering heterogeneous XML schemas.
New constructions of fuzzy identity-based encryption

In this paper we construct two new fuzzy identity-based encryption (IBE) schemes in the random oracle model. Not only do our schemes provide public parameters whose size is independent of the number of attributes in each identity (used as public key) but they also have useful structures which result in more efficient key extraction and/or encryption than the random oracle version of Sahai and Water's fuzzy IBE scheme, considered recently by Pirretti et al. We prove that the confidentiality of the proposed schemes is relative to the Bilinear Decisional Bilinear Diffie-Hellman problem.
Neighbour selection protocol for information dissemination through P2P interactions in opportunistic network

he absence of network topology knowledge in Opportunistic Network makes information dissemination the most compelling research issue. Communication routes evolve when information is forwarded from source to destination during node interactions. The communications between nodes in Opportunistic Networks are supported through mobility of mobiJe nodes. The connections between mobile nodes are often disconnected. However, information can still be disseminated through the opportunistic connections which are computed dynamically Ideally, in Opportunistic Network when two nodes are in communication range, they should pair-wise identify each other. This process potentially facilitates the formulation of social relationship between those two nodes which later can be used to identify the best possible forwarder to deliver the information. However, formulation of the social relationship between neighbouring nodes and selection of the appropriate node to forward information in Opportunistic Network are not trivial processes. Flooding is the best technique to disseminate the information in Opportunistic Network, because it achieves high delivery ratios, minimize message latency and does not require any pre-existing network infrastructure. However flooding approach suffers from high message overhead due to forwarding the information to all nodes. Considering the advantage of high delivery ratios of flooding, we proposed and designed the social based Neighbour Selection Protocol (NSP). The NSP uses Frequency in Range (FIR) and Frequency of Interaction (FOI) to assist the selection process. Each selected node in turn uses NSP to select a neighbouring node in order to disseminate information towards the destination. From the experimental results, we found that NSP can reduce the overhead and has delivery ratios close to flooding technique.
Machine learning for inferring phase connectivity in distribution networks

The connectivity model of a power distribution network can easily become outdated due to system changes occurring in the field. Maintaining and sustaining an accurate connectivity model is a key challenge for distribution utilities worldwide. This work focuses on inferring customer to phase connectivity using machine learning techniques. Using voltage time series measurements collected from customer smart meters as the feature set for training classifiers, we study the performance of supervised, semi-supervised and unsupervised techniques. We report analysis and field validation results based on real smart meter measurements collected from three feeder circuits of a large distribution network in North America.
Identification of prothymosin-α1, the necrosis–apoptosis switch molecule in cortical neuronal cultures

We initially identified a nuclear protein, prothymosin-α1 (ProTα), as a key protein inhibiting necrosis by subjecting conditioned media from serum-free cultures of cortical neurons to a few chromatography steps. ProTα inhibited necrosis of cultured neurons by preventing rapid loss of cellular adenosine triphosphate levels by reversing the decreased membrane localization of glucose transporters but caused apoptosis through up-regulation of proapoptotic Bcl2-family proteins. The apoptosis caused by ProTα was further inhibited by growth factors, including brain-derived neurotrophic factor. The ProTα-induced cell death mode switch from necrosis to apoptosis was also reproduced in experimental ischemia-reperfusion culture experiments, although the apoptosis level was markedly reduced, possibly because of the presence of growth factors in the reperfused serum. Knock down of PKCβII expression prevented this cell death mode switch. Collectively, these results suggest that ProTα is an extracellular signal protein that acts as a cell death mode switch and could be a promising candidate for preventing brain strokes with the help of known apoptosis inhibitors.
Adaptive Cluster Throttling: Improving High-Load Performance in Bufferless On-Chip Networks

Higher core counts and increasing focus on energy efficiency in modern Chip Multiprocessors (CMP) have led to renewed interest in simple and energy-efficient Network-on-Chip (NoC) designs. Several recent proposed designs trade off network capacity for efficiency, based on the observation that traditional networks are overprovisioned for many workloads. Bufferless routing is one such example. However, when the application workload requires high interconnect performance, the inefficiencies of bufferless interconnects can cause significant performance degradations. Previous work has tackled various issues with bufferless routing, but little work has been done to improve performance at high network load. Fundamental improvements in bufferless network performance at high load could extend the benefits of lower energy and smaller die area to a wider range of potential applications. In this work, we propose ACT (Adaptive Cluster Throttling), a source-throttling mechanism that provides better system performance and fairness than the best current mechanisms on bufferless networks. By batching applications into clusters, and alternately throttling different clusters, ACT provides a chance for all applications to inject traffic into the network while maintaining control over total network load. We show 11.9% (10.2%) system performance gain on average with 14.5% (15.1%) improvement in fairness over 60 network-intensive workloads on a 4x4 (8x8) bufferless NoC. At high network load, ACT achieves nearly half the performance gain over a bufferless baseline that a conventional buffered network achieves, while reducing network power by 15.4% (5.4%).
THE DOUBLE INTERPOLATION AND DOUBLE PREDICTION (DIDP) APPROACH FOR INSAR AND GPS INTEGRATION

The technique of synthetic aperture radar interferometry (or InSAR) was first suggested in 1974. Due to its characteristics of very high spatial resolution and wide coverage, as well as the cost effectiveness of the technique, it is not surprising that many earthquake ruptures have been studied using InSAR. However, InSAR is very sensitive to errors such as atmospheric effects, satellite orbit error, the condition of the ground surface and temporal decorrelation. Furthermore the repeat cycle of 35 (ERS-1) to 44 (JERS-1) days for SAR satellites cannot provide sufficient temporal resolution for some applications. On the other hand, many Continuous GPS (CGPS) networks of receivers have been established in recent years. CGPS can provide temporally dense observations (e.g. sampling at an interval of 30 seconds or higher), but these GPS receivers, spaced at about 25km apart for the densest arrays, are not spatially dense enough to characterise the dynamics of seismic faults. These require sub- kilometre level spatial resolution. Therefore, the two techniques of InSAR and CGPS appear to be very complementary. The proposed Double Interpolation and Double Prediction (DIDP) approach can be used to integrate InSAR and GPS results. The first step is to derive atmospheric corrections to the InSAR images from CGPS data, using techniques borrowed from 'GPS meteorology'. The second step is to remove or mitigate SAR satellite orbit errors by using the GPS results as constraints. These atmospheric and orbit corrections generate a GPS-corrected InSAR result. In the third step, the CGPS observations separated by one or several InSAR repeat cycles are densified in a grid manner by interpolation in the spatial domain, based on the GPS-corrected InSAR results; and then the densified grid observations are interpolated in the time domain using the daily, hourly, or even 30 second sampling rate of the CGPS time series. In the fourth step, based on the double interpolation result of the third step, forward filtering is used to predict the crustal deformation at all points on the grid. This is in fact a double prediction in both the temporal and spatial domains. Some algorithms and preliminary results of the DIDP technique for integrating InSAR and GPS results will be presented in this paper.
Comparison with Magnetic Resonance Three-Dimensional Sequence for Lumbar Nerve Root with Intervertebral Foramen

Study Design Prospective study based on magnetic resonance (MR) imaging of the lumbar spinal root of the intervertebral foramen. Purpose This study was to compare MR three-dimensional (3D) sequences for the evaluation of the lumbar spinal root of the intervertebral foramen. Overview of Literature The diagnosis of spinal disorders by MR imaging is commonly performed using two-dimensional T1- and T2-weighted images, whereas 3D MR images can be used for acquiring further detailed data using thin slices with multi-planar reconstruction. Methods On twenty healthy volunteers, we investigated the contrast-to-noise ratio (CNR) of the lumbar spinal root of the intervertebral foramen with a 3D balanced sequence. The sequences used were the fast imaging employing steady state acquisition and the coherent oscillatory state acquisition for the manipulation of image contrast (COSMIC). COSMIC can be used with or without fat suppression (FS). We compared these sequence to determine the optimized visualization sequence for the lumbar spinal root of the intervertebral foramen. Results For the CNR between the nerve root and the peripheral tissue, these were no significant differences between the sequences at the entry of foramen. There was a significant difference and the highest CNR was seen with COSMIC-FS for the intra- and extra-foramen. Conclusions In this study, the findings suggest that the COSMIC-FS sequences should be used for the internal or external foramen for spinal root disorders.
Application of Wearable Inertial Sensors in Ecological Rehabilitation Environments

Rehabilitation after injury or stroke is a long process towards regaining functionality, mobility, and independence. Changes exhibited in these areas tend to be subtle and are highly dependent on the patient and their injury. To provide a fine-grained assessment of patient progress, we undertook a study to quantitatively capture movements during inpatient rehabilitation. We utilized wearable inertial sensors to collect data from participants receiving physical therapy at an inpatient rehabilitation facility. Participant performance was recorded in an ecological environment on a sequence of ambulatory tasks. A custom software system was developed to process sensor signals and compute metrics describing ambulation. A comparison of metrics one week apart suggests quantifiable changes in movement. Author
On Non-Linearities Between Exports of Manufactures and Economic Growth

Building up human capital and other complementarities may be important in the link between exports of manufactures and economic growth. On the other hand, managerial strategies that push for export promotion may be important, too. Though both may yield non-linearities in the link between exports and growth, the associated patterns differ. In this paper we take an aseptic, empirical view in the link between these two variables and the possible nonlinear links. Since direct testing for non-linearities in panel data may yield non-significant results although they may actually be present, we propose a very simple method that may serve as a first approximation to uncover such non-linearities. We also take into consideration endogeneity and reverse causality problems (Arellano and Bover, 1995), and definitional problems in our variable of interest. In fact, we use a panel of 96 countries for the period 1960–1995 and find evidence consistent with the presence of non-linearities. We apply formal sensitivity analysis and confirm the results.
Deterministic Consistency: A Programming Model for Shared Memory Parallelism

The difficulty of developing reliable parallel software is generating interest in deterministic environments, where a given program and input can yield only one possible result. Languages or type systems can enforce determinism in new code, and runtime systems can impose synthetic schedules on legacy parallel code. To parallelize existing serial code, however, we would like a programming model that is naturally deterministic without language restrictions or artificial scheduling. We propose deterministic consistency, a parallel programming model as easy to understand as the “parallel assignment” construct in sequential languages such as Perl and JavaScript, where concurrent threads always read their inputs before writing shared outputs. DC supports common data- and task-parallel synchronization abstractions such as fork/join and barriers, as well as non-hierarchical structures such as producer/consumer pipelines and futures. A preliminary prototype suggests that softwareonly implementations of DC can run applications written for popular parallel environments such as OpenMP with low (< 10%) overhead for some applications.
Combining a Temporal Planner with an External Solver for the Power Balancing Problem in an Electricity Network

The electricity network balancing problem consists of ensuring that the electricity demands of the consumers are met by the committed supply. Constraints are imposed on the different elements of the network, so that damage to the equipment is prevented when transformers are stepped up or down, or generation is increased. We consider this problem within zones, which are sub-networks constructed using carefully chosen decomposition principles. The automation of decision making in electricity networks is a step forward in their management which is necessary for coping with the increase in power system complexity that we expect in the near term. In this paper we explore the deployment of planning techniques to solve the zone-balancing problem. Embedding electricity networks in a domain description presents new challenges for planning. The key point is that the propagation of information requires complex updates to the state when an action is applied. We have developed a method in which the computation of the critical numeric quantities is performed calling an external power flow equation solver, demonstrating a clean interface between the planner and this domain-specific computation. This solver allows us to move the power flow computations outside of the planning process and update the values efficiently. We also examine a second important feature of this problem, which is the interaction between exogenous events and constraints over the entire plan trajectory within a zone.