Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability in the Middle Stone Age of Eastern Africa

Eastern Africa is an important area to study early populations of Homo sapiens because subsets of those populations likely dispersed to Eurasia and subsequently throughout the globe during the Upper Pleistocene. The Middle Stone Age (MSA) archaeology of this region, particularly aspects of stone-tool technology and typology, is highly variable with only rare cases of geographic and temporal patterning. Although there are differences in timing and perhaps frequency of occurrence, those elements that make up the MSA lithic tool kit are also found at contemporaneous sites elsewhere in Africa and Eurasia, making it difficult to identify a unique archaeological signal for hominin dispersals out of eastern Africa. Rather, regional variation appears to be the outcome of possibly long-term interactions between particular physical and social environments experienced by hominin populations.
Concurrent Flip-flop and Buffer Insertion under Pipeline Constraint*

In complex digital systems with high operating frequencies and large chip sizes, concurrent flip-flop and buffer insertion becomes inevitable for interconnect optimization. To preserve functional integrity, the pipeline constraint must be satisfied. Moreover, blockage avoidance, power reduction, and timing margin increase are also important issues. In this paper, we study the problem of blockage-aware concurrent flip-flop and buffer insertion for latency minimization while satisfying the pipeline constraint. We also consider power dissipation or timing margin as the second objective to optimize. We present two algorithms to solve the problem, one for simultaneous minimization of latency and power dissipation and the other for simultaneous optimization of latency and timing margin. In comparison with an approach, called MiLa+GiLa [2], our algorithms are able to find a solution with the same or even smaller latency for each test case. Besides, our algorithms can reduce power by up to 9% and increase timing margin by 6X as compared to MiLa+GiLa.
Similar Subtree Search Using Extended Tree Inclusion

This paper considers the problem of identifying all locations of subtrees in a large tree or in a large collection of trees that are similar to a specified pattern tree, where all trees are assumed to be rooted and node-labeled. The tree edit distance is a widely-used measure of tree (dis-)similarity, but is NP-hard to compute for unordered trees. To cope with this issue, we propose a new similarity measure which extends the concept of unordered tree inclusion by taking the costs of insertion and substitution operations on the pattern tree into account, and present an algorithm for computing it. Our algorithm has the same time complexity as the original one for unordered tree inclusion, i.e., it runs in O(|T1∥T2|) time, where T1 and T2 denote the pattern tree and the text tree, respectively, when the maximum outdegree of T1 is bounded by a constant. Our experimental evaluation using synthetic and real datasets confirms that the proposed algorithm is fast and scalable and very useful for bibliographic matching, which is a typical entity resolution problem for tree-structured data. Furthermore, we extend our algorithm to also allow a constant number of deletion operations on T1 while still running in O(|T1∥T2|) time.
Emergence of Individuality and Sociality by Reinforcement Learning in Multi-Agent Systems

In this paper, a new viewpoint, "individuality" and "sociality", is introduced for analyzing the multi-agent system's behavior. A hypothesis is set up that the both behavioral characters emerge to generate different actions from the other agent to increase each agent's bene t. "Individuality" is de ned as the di erence of actions between agents based on the di erence of its internal information processing. While "sociality (rule)" is de ned as the di erence of actions based on the di erence of its sensory inputs. Next, a model is proposed in which "individuality" and "sociality" are obtained by reinforcement learning. It is also mentioned that there exist some factors like asymmetry of the environment, which in uence the di erentiation into one of the two characters. Finally through some simulations of con ict avoidance problems among passengers getting on and o a train, it is examined that the di erentiation is adaptive to some of the above factors appropriately, and the rule that the passengers getting o have a priority to go.
A robust image watermarking algorithm based on non-uniform rectangular partition and encryption scrambling

The watermark is more likely to prevent itself from JPEG-compression attack when it is embedded into the DC values of 8×8 DCT blocks. However, embedding the watermark with the same intensity into the DC values of DCT blocks may distort the watermarked image to a large extent. To solve this problem, a novel robust image-watermark algorithm is proposed with the characteristics of selective embedding intensity based on the non-uniform partition. Firstly, following the rectangular partition algorithm, the image has automatically been partitioned into different rectangles which reflect the grey-distribution characteristics in different dimensions. Secondly, the suitable embedded intensities have been chosen, according the number of rectangles within each 8×8 block. Meanwhile, in order to increase the anti-cropping function and the security of the algorithm, MUST∗ Encryption Algorithm is applied to encrypt the pixel-locations of the watermark before the watermark is embedded. The results of the experiments have showed that this algorithm is robust against noising attack, cropping attack, especially the JPEG-compression attack and no obvious distortion appeared in the watermarked image.
Fads versus Fundamentals in Farmland Prices: Comment

A trivariate vector autoregression time series process, based on a present-value land price model, is used to decompose Iowa farmland prices into fundamental and non-fundamental components. A recent study, by Falk and Lee (1998), found that non-fundamental shocks are an important source of volatility in farmland prices and it was interpreted that these price movements were due to fads not speculative bubbles. We argue to the contrary and use a regime-switching model to provide evidence that supports a partially collapsing bubble story of the dynamics of Iowa farmland prices.
The "ecoGator" app: gamification for enhanced energy efficiency in Europe

In the course of the IEE (Intelligent Energy Europe) funded project "Efficiency 2.1 - New Media for top informed consumers regarding sustainable and energy efficient products" a consortium of 12 partners (led by the Austrian Energy Agency) from 10 European countries is charged with designing, developing and rolling out an "Efficiency adviser" smartphone application named "ecoGator". The main objective of the "ecoGator" app is to support consumer awareness of energy efficient purchase and use of products, enhancing energy-aware and ecologically sound behavior in everyday life. To reach that goal it is crucial to encourage consumers to use this application regularly. This paper describes the evaluation of the gamification strategy of the app "ecoGator". With a qualitative assessment (usability testing method) the gamification elements were tested in terms of motivation, understanding and ease of use. The results of the tests will be considered in the ongoing developing phase of the application and should support the ambitious project targets.
Wage Rigidity and Monetary Union

We compare monetary union to flexible exchange rates in an asymmetric, three-country model with active monetary policy. Unlike Friedman's (1953) case for flexible rates, we find that countries with high degree of nominal wage rigidity are better off in a monetary union. Their benefits increase with the size of the union and the degree of wage rigidity of its members. Those with relatively more flexible wages fare better under a flexible rate regime. Their cost of participation in a monetary union increases with the union's level of wage rigidity as well as its tolerance of inflation variability. Taking into account actual asymmetries in the EU we find that the status quo (France and Germany in EMU, the UK pursuing a flexible rate) represents the best monetary arrangement for each of these countries. All three would likely be worse off if the UK joined EMU.
What Is Extraversion For? Integrating Trait and Motivational Perspectives and Identifying the Purpose of Extraversion

The purpose of this study was to determine whether the manifestation of extraversion (i.e., acting and being extraverted) in everyday behavior can be explained by intentional (functional) constructs, namely, goals. By using a model in which personality states serve as an outcome of specific, momentary goal pursuit, we were able to identify the function of extraversion states in everyday behavior. Using experience-sampling methodology, we asked participants to describe their state extraversion, goal pursuit, and state affect over 10 days. Results show that 18 selected goals predicted 74% of the variance in state extraversion; both within-person and between-person fluctuations in state extraversion were strongly associated with changes in momentary goal pursuit. We extended findings relating state extraversion and state positive affect, showing that the relationship between goals and positive affect was partially mediated by state extraversion.
How attention to everyday technology could contribute to modern occupational therapy: A focus group study

Introduction Everyday technologies such as mobile phones and ticket vending machines have become increasingly indispensable, profoundly influencing daily life activities. Yet this has been given little attention in occupational therapy. The aim of this study was to explore occupational therapists’ views on everyday technologies’ relevance, meaning and potential applicability in practice. Method Focus groups were undertaken with 42 occupational therapists who had been introduced to an assessment of people’s ability to use everyday technologies. Data comprised eight focus groups and were analysed with a constant comparative approach. Findings The findings show how the participants’ fields of vision expanded when they discovered new ways of using information related to their clients’ everyday technology use, and new roles as therapists that would help make occupational therapy ‘modern’, that is, more timely and up-to-date. However, this also implied a risk of receiving information that was considered potentially unethical if the detected problems could not be dealt with. Conclusion Attending to clients as everyday technology users could give occupational therapists new expert roles, and allow clients to be seen as more complete persons. However, as this opportunity also involves priority conflicts and ethical dilemmas, the issue can inspire critical discussion about client-centred occupational therapy.
Hierarchical speaker identification using speaker clustering

We explore an approach to speaker identification called speaker clustering in the GMM-based speaker recognition system in order to reduce the computational complexity. The ISODATA algorithm adapted for our purpose works well when we cluster speakers whose acoustic characteristics are similar to a distance measure. The time spent on HSI (hierarchical speaker identification) is approximately 30.3 percent more than that spent on CSI (conventional speaker identification) when the number of registered speakers is 40 in our experiments. Increasing of the number of speakers decreases the time spent on HSI compared with CSI. It is shown that this approach can improve the speed of the speaker identification system.
Probabilistic Zero-shot Classification with Semantic Rankings

In this paper we propose a non-metric ranking-based representation of semantic similarity that allows natural aggregation of semantic information from multiple heterogeneous sources. We apply the ranking-based representation to zero-shot learning problems, and present deterministic and probabilistic zero-shot classifiers which can be built from pre-trained classifiers without retraining. We demonstrate their the advantages on two large real-world image datasets. In particular, we show that aggregating different sources of semantic information, including crowd-sourcing, leads to more accurate classification.
Empirical Study on Regional Logistics Industry's Competitiveness Based on Factor Analysis

Logistics industry has been developing rapidly in China, but it is still a fledgling industry. Some Chinese scholars have made considerable researches on it, but the study in this field has been at the initial stage so far. On the basis of previous studies, we establish a more comprehensive and objective evaluation indicator system on the principles of all-around perspectives, close relationship and data accessibility and then use factor analysis method and statistics of 2006 to do empirical study by SPSS software on the logistics industry's competitiveness in 30 provinces, municipalities and autonomous regions in China. The analysis result suggests that the logistics industries in some regions are effective, as there are heavy demands for logistics services, but unfavourable logistics condition; meanwhile, some regions have much potential in the development of logistics industries, which are weak in competitiveness mainly because of weak demand for logistics services at present.
Structure-based calculation of drug efficiency indices

MOTIVATION The efficiency indices (EI's) have been derived from the experimental binding affinities of drug candidates to macromolecules. These 'two-in-one' measures include information on both pharmacodynamics and pharmacokinetics of the candidate molecules. The time-consuming experimental measurement of binding affinities of extensive molecule libraries may become a bottle-neck of large scale generation and application of EI's. RESULTS To overcome this limitation, structure-based calculation of new EI's is introduced using the modified free energy function of the popular program package AutoDock. The results are validated on experimental binding data of biochemical systems such as potent inhibitors bound to beta-secretase, a key enzyme of Alzheimer's disease and various drug-protein complexes. Application of new EI's is tested. Thermodynamics of EI's and their role in virtual high-throughput screening of drugs and in the development of docking programs are discussed. SUPPLEMENTARY INFORMATION Accompanies this manuscript on the publisher's web site.
Accelerating Immunos 99

Immunos 99 is a classification algorithm based upon the principles of Artificial Immune Systems (AIS). AIS algorithms can provide alternatives to classical techniques such as decision trees for classification tasks. Immunos 99 provides one alternative however the algorithm and implementations have some room for performance improvement. This paper discusses improvements made to Immunos 99 and its reference implementation to improve runtime performance. The new algorithm/implementation results in an approximate 40% reduction in run time on test data. The paper closes with a proposal for an implementation of the Immunos 99 algorithm that is suitable for use on map/reduce clusters.
Reliability and Validity Study on the Korean Version of the Fullerton Advanced Balance Scale

Background: The assessment tool developed in other countries should be translated into Korean language using rigorous methodological approaches in order to be used in Korea. Because these procedures are insufficient for establishing the cross-cultural and linguistic equivalence, the need for statistical methods is raised. The Fullerton Advanced Balance Scale was translated into Korean and the content validity was verified through the back translation method, but the reliability and validity have not yet been proven by statistical methods. Objects: The purpose of this study was to investigate the reliability and validity of the Korean version of the Fullerton Advanced Balance Scale (KFAB) by statistical methods in elderly people. Methods: A total of 97 elderly adults (39 males and 58 females) participated in this study. Internal consistency of the KFAB was measured using Cronbach's alpha and an intraclass correlation coefficient (ICC) was used to assess test-retest reliability between the two measurement sessions. Concurrent validity was measured by comparing the KFAB responses with the Korean version of the Berg Balance Scale (KBBS) using the Spearman correlation coefficient. Construct validity of the KFAB was measured using the exploratory factor analysis to evaluate the unidimensionality of the questionnaire. The significance level was set at . Results: The internal consistency of the KFAB was found be adequate with Cronbach's alpha (.96), and test-retest reliability was excellent as evidenced by the high ICC (r=.996). Concurrent validity showed high correlation between the KFAB and KBBS (r=. 89, p
Cloud API issues: an empirical study and impact

Outages to the cloud infrastructures have been widely publicized and it would be easy to conclude that application developers only need to be concerned with large scale cloud provider infrastructure outages. Unfortunately, this is not the case. In-cloud applications heavily rely on cloud infrastructure APIs (directly or indirectly through scripts and consoles) for many sporadic activities such as deployment change, scaling out/in, backup, recovery and migration. Failures and/or issues around API calls are a large source of faults that could lead to application failures, especially during sporadic activities. Infrastructure outages can also be greatly exacerbated by API-related issues. In this paper we present an empirical study of issues in Amazon EC2 APIs. Some of the major findings around API issues include: 1) A majority (60%) of the cases of API failures are related to "stuck" API calls or unresponsive API calls. 2) A significant portion (12%) of the cases of API failures are about slow responsive API calls. 3) 19% of the cases of API failures are related to the output issues of API calls, including failed calls with unclear error messages, as well as missing output, wrong output, and unexpected output of API calls. 4) There are 9% cases of API failures reporting that their calls (performing some actions and expecting a state change) were pending for a certain time and then returned to the original state without informing the caller properly or the calls were reported to be successful first but failed later. We also classify the causes of API issues and discuss the impact of API issues on application architectures.
Reduced variability in pulse wave velocity in depressed patients with suicidal ideation

Recently arterial stiffness was found to be associated with depression. The aim of this study was to investigate the association between arterial pulse wave velocity (PWV) and Major Depressive Disorder (MDD) with or without suicidal ideation. Twenty unmedicated MDD patients with a history of suicidal ideations (Age: 32.37±9.53 years) and 20 unmedicated MDD patients without any history of suicidal ideations (Age: 36.84±8.66) were recruited for this study at a psychiatric clinic in the UAE. Depression severity was assessed with the Hamilton Depression Rating Scale and the Beck Depression Inventory. Pulse wave velocity (PWV) was estimated from the ratio of half of the height and Pulse Transit Time which is defined as the time delay between the R-wave of the ECG and the arrival of the pulse wave in the index finger respectively. MDD Patients with suicidal ideation were found to have reduced low frequency (LF) and high frequency (HF) power of PWV compared to MDD patients without suicidal ideations. Suicidal score was negatively correlated (r=-0.54;p<;0.05) with LF power and positively (r=0.54; p<;0.01) with HF power. No difference in the average PWV was found between the two groups of participants. Reduced variability in pulse wave velocity in MDD patients with suicidal ideation may lead to arterial stiffness and higher risk of future cardiovascular disease.
Computing and mental health: intentionality and reflection at the click of a button

Automated passive sensing applications and self-reported smart diaries seem to hold promise for the management of anxiety in autism and other mental health conditions. However, passive sensing often struggles with noisy data, ambiguous feedback and weak user agency over the device, whilst self-reporting relies on user-entered data which can be time consuming and cognitively demanding. To address these limitations, we explore a different approach, whereby individuals consciously actuate personal data capture and are in control of it at all times; yet, the interaction solely involves clicking a button, thus avoiding cognitive overload whilst supporting immediate reflection. We call this approach intentive computing. Through our initial investigations we found that conscious interactions cannot only provide real-time relief in anxiety management, but can also function as memory anchors irrespective of the content captured and even prior to data visualization.
On the Fraction of X-Ray-obscured Quasars in the Local Universe

Recent wide-area hard X-ray and soft gamma-ray surveys have shown that the fraction of X-ray-obscured active galactic nuclei (AGNs) in the local universe significantly decreases with intrinsic luminosity. In this Letter we point out that two corrections have to be made to the samples: (1) radio-loud AGNs have to be excluded, since their X-ray emission might be dominated by the jet component, and (2) Compton-thick sources have to be excluded too, since their hard X-ray and soft gamma-ray emission are also strongly attenuated by Compton scattering. The soft gamma-ray-selected AGN samples obtained by Swift and INTEGRAL provide the best opportunity to study the fraction of obscured AGNs in the local universe in the least biased way. We choose these samples to check if the corrections could alter the above result on the fraction of obscured AGNs. We find that before the corrections both samples show significant anticorrelation between LX and NH, indicating an obvious decrease in the fraction of obscured AGNs with luminosity. However, after the corrections, we find only marginal evidence of anticorrelation (at the 98% confidence level) in the Swift sample and no evidence at all in the INTEGRAL sample, which consists of a comparable number of objects. We conclude that current samples only show a marginal decrease in the fraction of obscured AGNs in the local universe and that much larger samples are required in order to reach a more robust conclusion.
A time-indexed formulation for single-machine scheduling problems : column generation

Time indexed formulations for single machine scheduling problems have received a lot of attention because the linear program relaxations provide strong bounds Unfortunately time indexed formulations have one major disadvantage their size Even for relatively small instances the number of constraints and the number of variables can be large In this paper we discuss how Dantzig Wolfe decomposition techniques can be applied to alleviate the di culties associated with the size of time indexed formulations and that the application of these techniques still allows the use of cut generation techniques