Miracle-dz/UniFAR-FTUs huggingface dataset:
U‐Pb Zircon Ages of Granitoid Rocks in the North Dabie Complex, Eastern Dabie Shan, China

The North Dabie Complex (NDC) comprises a high‐temperature metamorphic suite dominated by amphibolite‐facies granitoid orthogneiss intruded by voluminous granites. U‐Pb zircon dating on these rocks yields the following new results: (1) Two of the granitoid orthogneiss samples have Early Cretaceous protolith emplacement ages of 133.7 ± 2.3 Ma and 134.0 ± 2.8 Ma. (2) an undeformed granodiorite intrusive into granitoid gneiss yields an emplacement age at 125.6 ± 0.3 Ma. These Early Cretaceous ages entirely post‐date Late Triassic‐Early Jurassic continental subduction and exhumation evident in the neighboring ultrahigh and high‐pressure metamorphic terrains to the south in the Dabie Shan; hence they do not support previous tectonic models that infer Paleozoic or Triassic protolith emplacement ages for these granitoid orthogneisses. (3) A mylonitic granite from the northern boundary of the NDC yields a concordant age of 756.6 ± 0.8 Ma, which is interpreted as magma emplacement age. The concordance of this Late Proterozoic age suggests that the U‐Pb systematics have not been disturbed by any significant thermal overprint since emplacement, implying that the northern extent of the deeply subducted Yangtze Block lies south of this locality.
Edinburgh System Description for the 2005 IWSLT Speech Translation Evaluation

Our participation in the IWSLT 2005 speech translation task is our first effort to work on limited domain speech data. We adapted our statistical machine translation system that performed successfully in previous DARPA competitions on open domain text translations. We participated in the supplied corpora transcription track. We achieved the highest BLEU score in 2 out of 5 language pairs and had competitive results for the other language pairs.
E-Governance and Development: Service Delivery to Empower the Poor

This article provides a quick assessment of current e-governance policies and programmes to then suggest an alternative approach to the issue of the use information and communications technology in governance process. By focusing on citizens and stakeholders needs and fostering their participation in decision-making processes, governments can be best prepared to provide them with basic services and information, especially to poor and marginalized areas excluded from the potential benefits of e-governance. Pro-poor basic delivery in turn has the potential of fostering stakeholder engagement in public policy discussions at the local level.
Effect of Vegetation on Banks on Distributions of Velocity and Reynolds Stress under Accelerating Flow

Vegetation on banks of natural channels exercises a significant influence on the flow structure and in turn on the velocity distribution as well as the distribution of Reynolds stress (the random turbulent fluctuations in fluid momentum). This study experimentally investigated the effect of vegetation on banks on accelerating flow in a gravel-bed flume. The results showed that in the presence of vegetation the Reynolds stress distribution became nonlinear and the velocity distribution took on a deformed S shape near the vegetated banks. In addition, vegetation on banks had more influence on the location of maximum velocity than had the aspect ratio. The log law fitted the data near the bed up to y/h=0.2 ( h=flow depth and y=distance from the bed), however, very near the bed the scatter in data was significant. Finally, the Coles law cannot be applied for accelerating flow when the vegetation was present on banks.
Uncertainty-Aware Off-Policy Learning

Oﬀ-policy learning, referring to the procedure of policy optimization with access only to logged feedback data, has shown importance in various real-world applications, such as search engines, recommender systems, and etc. While the ground-truth logging policy, which generates the logged data, is usually unknown, previous work simply takes its estimated value in oﬀ-policy learning, ignoring both high bias and high variance resulted from such an estimator, especially on samples with small and inaccurately estimated logging probabilities. In this work, we explicitly model the uncertainty in the estimated logging policy and propose a Uncertainty-aware Inverse Propensity Score estimator (UIPS) for improved oﬀ-policy learning. Experiment results on synthetic and three real-world recommendation datasets demonstrate the advantageous sample eﬃciency of the proposed UIPS estimator against an extensive list of state-of-the-art baselines.
Responding to land degradation in the highlands of Tigray, Northern Ethiopia

Improving the long-term sustainability and resilience of smallholder agriculture in Africa is highly dependent on conserving or improving the quality of the natural resource. Conservation agriculture is conceived around more integrated and effective management strategies for provisioning both food and other ecosystem services. If unattended to, land degradation would reduce agricultural productivity and increase pressure on marginal environments in the Tigray highlands of Ethiopia, adversely affecting food security and livelihoods of smallholder farmers. This paper answers some pertinent questions about mass mobilization of free compulsory labor for ecological restoration in Tigray. It details perception of changes in climate; the process of collective decisionmaking; resistance, documentation, and enforcement of rules; methods of conflict resolution; knowledge and information networks; arrangements for benefit sharing of communal resources; and the role of gender in mass mobilization for communal work. We analyzed data collected from 20 villages in 3 districts in the Tigray region through a household survey using a structured questionnaire, focus group discussions, and personal observations. The results reveal that the people are motivated to provide their free labor to restore the ecology to increase agricultural productivity and production to avoid food insecurity and improve their general livelihood. Availability of institutions in terms of grassroots organizations and rules and regulations was a major factor in the positive response to the call for action. The commitment of the government at both the national and local levels (through sensitization and mobilization for group formation and provision of tools and construction materials); the ethnic homogeneity of the population; and the existence of the Orthodox Church, where most of the people were members, were major factors for the success of the community mobilization for collective action in Tigray. Social networking with neighbors, the clergy, and leaders of grassroots organizations provided the knowledge and information on climate variability and solutions required to conserve the ecology and improve human livelihood. We also observed that there were no differences in gender division of labor except that women worked half the workload of men in a day; the women also did the cooking and cleaned up the surroundings after eating at the site. Both men and women played active roles in leadership with regard to mobilization of people, communal work planning and scheduling, conflict resolution, and sharing of community products. An impact assessment of the ecological conservation in Tigray on agricultural productivity and production and food security would be useful. It will be interesting to replicate the study in other areas in Ethiopia and other countries where the societies may not be homogenous to find out the level of commitment of the people to communal work.
Toward accurate CO2 and CH4 observations from GOSAT

The column‐average dry air mole fractions of atmospheric carbon dioxide and methane and are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground‐based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for and with a station‐to‐station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root‐mean square deviation of the bias‐corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for and 0.015 ppm for Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of suggesting the use of the satellite retrievals for constraining surface fluxes.
User behaviours after critical mobile application incidents: the relationship with situational context

Users occasionally have critical incidents with information systems (IS). A critical IS incident is an IS product or service experience that a user considers to be unusually positive or negative. Critical IS incidents are highly influential in terms of users' overall perceptions and customer relationships; thus, they are crucial for IS product and service providers. Therefore, it is important to study user behaviours after such incidents. Within IS, the relationships between the situational context and user behaviours after critical incidents have not been addressed at all. Prior studies on general mobile use as a related research area have recognized the influence of the situational context, but they have not covered the relationships between specific situational characteristics and different types of user behaviours. To address this gap, we examine 605 critical mobile incidents that were collected from actual mobile application users. Based on our results, we extend current theoretical knowledge by uncovering and explaining the relationships between specific situational characteristics (interaction state, place, sociality and application type) and user behaviours (use continuance, word‐of‐mouth and complaints). We have found, for example, that users are less likely to engage in negative behaviours after negative incidents that take place outdoors or in vehicles than after indoor incidents. This is because users often consider indoor environments to be familiar and treat them with established expectations and low uncertainty: users are accustomed to the notion that the applications function indoors just like before. Further, we present practical implications for mobile application providers by suggesting to them which positive critical incidents are the most beneficial to promote and which negative critical incidents are the most crucial to avoid.
Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models

We develop a convex analytic framework for ReLU neural networks which elucidates the inner workings of hidden neurons and their function space characteristics. We show that rectiﬁed linear units in neural networks act as convex regularizers, where simple solutions are encouraged via extreme points of a certain convex set. For one dimensional regression and classiﬁcation, we prove that ﬁnite two-layer ReLU networks with norm regularization yield linear spline interpolation. In the more general higher dimensional case, we show that the training problem for two-layer networks can be cast as a convex optimization problem with inﬁnitely many constraints. We then provide a family of convex relaxations to approximate the solution, and a cutting-plane algorithm to improve the re-laxations. We derive conditions for the ex-actness of the relaxations and provide simple closed form formulas for the optimal neural network weights in certain cases. Our results show that the hidden neurons of a ReLU network can be interpreted as convex autoen-coders of the input layer. We also establish a connection to (cid:96) 0 - (cid:96) 1 equivalence for neural networks analogous to the minimal cardinality solutions in compressed sensing. Extensive experimental results show that the proposed approach yields interpretable and accurate models.
Galois groups and factoring polynomials over finite fields

Let p be a prime and F be a polynomial with integer coefficients. Suppose that the discriminant of F is not divisible by p, and denote by m the degree of the splitting field of F over Q and by L the maximal size of the coefficients of F. Then, assuming the generalized Riemann hypothesis (GRH), it is shown that the irreducible factors of F modulo p can be found in deterministic time polynomial in deg F, m, log p, and L. As an application, it is shown that it is possible under GRH to solve certain equations of the form nP=R, where R is a given and P is an unknown point of an elliptic curve defined over GF(p) in polynomial time (n is counted in unary). An elliptic analog of results obtained recently about factoring polynomials with the help of smooth multiplicative subgroups of finite field is proved. <<ETX>>
Meta Distribution of SIR in Large-Scale Uplink and Downlink NOMA Networks

We develop an analytical framework to derive the meta distribution and moments of the conditional success probability (CSP), which is defined as success probability for a given realization of the transmitters, in large-scale co-channel uplink and downlink non-orthogonal multiple access (NOMA) networks with one NOMA cluster per cell. The moments of CSP translate to various network performance metrics such as the standard success or signal-to-interference ratio (SIR) coverage probability (which is the 1-st moment), the mean local delay (which is the −1st moment in a static network setting), and the meta distribution (which is the complementary cumulative distribution function of the success or SIR coverage probability and can be approximated by using the 1st and 2nd moments). For the uplink NOMA network, to make the framework tractable, we propose two point process models for the spatial locations of the inter-cell interferers by utilizing the base station (BS)/user pair correlation function. We validate the proposed models by comparing the second moment measure of each model with that of the actual point process for the inter-cluster (or inter-cell) interferers obtained via simulations. For downlink NOMA, we derive closed-form solutions for the moments of the CSP, success (or coverage) probability, mean local delay, and meta distribution for the users. As an application of the developed analytical framework, we use the closed-form expressions to optimize the power allocations for downlink NOMA users in order to maximize the success probability of a given NOMA user with and without latency constraints. Closed-form optimal solutions for the transmit powers are obtained for two-user NOMA scenario. We note that maximizing the success probability with latency constraints can significantly impact the optimal power solutions for low SIR thresholds and favor orthogonal multiple access.
An Exploration of Prompt Tuning on Generative Spoken Language Model for Speech Processing Tasks

Speech representations learned from Self-supervised learning (SSL) models have been found beneficial for various speech processing tasks. However, utilizing SSL representations usually requires fine-tuning the pre-trained models or designing task-specific downstream models and loss functions, causing much memory usage and human labor. On the other hand, prompting in Natural Language Processing (NLP) is an efficient and widely used technique to leverage pre-trained language models (LMs). Nevertheless, such a paradigm is little studied in the speech community. We report in this paper the first exploration of the prompt tuning paradigm for speech processing tasks based on Generative Spoken Language Model (GSLM). Experiment results show that the prompt tuning technique achieves competitive performance in speech classification tasks with fewer trainable parameters than fine-tuning specialized downstream models. We further study the technique in challenging sequence generation tasks. Prompt tuning also demonstrates its potential, while the limitation and possible research directions are discussed in this paper.
Better Aligning Text-to-Image Models with Human Preference

Recent years have witnessed a rapid growth of deep generative models, with text-to-image models gaining significant attention from the public. However, existing models often generate images that do not align well with human aesthetic preferences, such as awkward combinations of limbs and facial expressions. To address this issue, we collect a dataset of human choices on generated images from the Stable Foundation Discord channel. Our experiments demonstrate that current evaluation metrics for generative models do not correlate well with human choices. Thus, we train a human preference classiﬁer with the collected dataset and derive a Human Preference Score (HPS) based on the classiﬁer. Using the HPS, we propose a simple yet effective method to adapt Stable Diffusion to better align with human aesthetic preferences. Our experiments show that the HPS outperforms CLIP in predicting human choices and has good generalization capability towards images generated from other models. By tuning Stable Diffusion with the guidance of the HPS, the adapted model is able to generate images that are more preferred by human users. The project page is available here: https://tgxs002.github. io/align sd web/.
Hydrologic alterations in the Wabash River watershed, USA

Flow alteration of streams from anthropogenic impacts is ubiquitous worldwide. In this paper, we examine flow alteration in a single watershed, the Wabash River and suggest potential impacts on aquatic assemblages. The Indicators of Hydrologic Alteration (IHA) software was used to evaluate hydrological variables generated from daily discharge data of 80 USGS gauging stations, during the past several decades. We used the approach of regressions of hydrological variables against time to identify hydrologic change. An average of 6.9 hydrologic variables (of 33 variables) were significantly altered at each station, and stations with larger watersheds had an increased number of altered variables. A principal components (PC) analysis of altered hydrologic variables resulted in three of four PC axes that were correlated with watershed area. Significant results were: (1) larger streams were more likely to have hydrologic alteration than smaller streams; (2) streams with upstream dams had increased minimum flows for 1‐, 3‐, 7‐ and 30‐day intervals, decreased maximum flows for 1‐, 3‐, 7‐ and 30‐day intervals, increased fall rates, decreased summer monthly flows and decreased high pulse counts; (3) the presence of agriculture in upstream watersheds resulted in an increased number of zero flow days, increased low pulse counts and decreased high flows during October and April. No significant differences were detected in hydrologic alteration based on urban land‐use of upstream watersheds. Hydrologic alterations in the Wabash River watershed have undoubtedly resulted in ecological degradation. We suggest that changes in assemblages during the past century are linked to these hydrologic alterations. Copyright © 2008 John Wiley & Sons, Ltd.
A Precipitation Seesaw Mode between Northeast Asia and Siberia in Summer Caused by Rossby Waves over the Eurasian Continent

Abstract There is a dominant seesaw pattern in summertime precipitation between northeast Asia and Siberia. Examined here is a mechanism of the seesaw mode, focusing on quasi-stationary Rossby waves propagating on two upper-tropospheric waveguides along the Asian jet and over northern Eurasia. Empirical orthogonal function (EOF) analysis to the low-frequency (10-day low-pass filtered) variation during summer reveals wave-propagation patterns on both of the waveguides. The time evolution of the two composite fields, constructed using the obtained EOF modes for each phase of the seesaw mode, was investigated by the wave-activity flux. In both composite fields, eastward-propagating Rossby waves originating from the North Atlantic–European sector branch off around eastern Europe onto the two waveguides, which become out of phase toward the east because of the difference in longitudinal wavelengths along them. This results in opposite phase anomalies of meridional winds over northeast Asia and Siberia. Budget .
Caractérisation de la pollution chimique et microbiologique de l\'environnement de la décharge d\'Akouédo, Abidjan-Côte d\'Ivoire

Durant ces dernieres annees, plusieurs cas de pollution des eaux de proximite ont ete signales dans la litterature. Afin de caracteriser la pollution chimique et microbiologique de l\'environnement de la decharge d\'Akouedo, des analyses physico-chimiques (metaux lourds et nutriments) et microbiologiques ont ete effectuees sur les lixiviats issus de la decharge. Le sol de la decharge a ete soumis a l\'analyse d\'une large gamme de metaux lourds (Fe, Cd, Cu, Zn, Mn, Pb, Hg, Cr, Mg). La composition du biogaz emanant de la decharge a ete egalement mesuree a partir de puits fores sur le site. Les concentrations des parametres (metaux, nutriments, indicateurs bacteriologiques, DBO5 et DCO) dans le lixiviat sont plus elevees que celles recommandees par le Centre Ivoirien Antipollution (CIAPOL) pour le rejet des effluents. On observe une forte concentration des metaux dans les sols de la decharge. Les valeurs basiques du pH du sol pourraient favoriser les phenomenes d\'absorption des metaux lourds et limiter leur migration vers les nappes d\'eau souterraine. Le biogaz emanant de la decharge est compose essentiellement de CH4 (70%) et de CO2 (29%). Le rapport CH4/CO2 est eleve, superieur a 2, ce qui traduit l‘anoxicite du milieu et sa grande capacite a produire le methane. La decharge d\'Akouedo constitue donc un important puits de production de gaz a effet de serre. Keywords : Lixiviat, contamination, metaux lourds, microbiologie, biogaz. International Journal of Biological and Chemical Sciences Vol. 2 (4) 2008: pp. 401-410
Fine-grained Poisoning Attacks to Local Differential Privacy Protocols for Mean and Variance Estimation

Local differential privacy (LDP) protects individual data contributors against privacy-probing data aggregation and analytics. Recent work has shown that LDP for some specific data types is vulnerable to data poisoning attacks, which enable the attacker to alter analytical results by injecting carefully-crafted bogus data. In this work, we focus on applying data poisoning attack to unexplored statistical tasks, i.e. mean and variance estimations. In contrast to prior work that aims for overall LDP performance degradation or straightforward attack gain maximization, our attacker can fine-tune the LDP estimated mean/variance to the desired target values and simultaneously manipulate them. To accomplish this goal, we propose two types of data poisoning attacks: input poisoning attack (IPA) and output poisoning attack (OPA). The former is independent of LDP while the latter utilizes the characteristics of LDP, thus being more effective. More intriguingly, we observe a security-privacy consistency where a small 𝜖 enhances the security of LDP contrary to the previous conclusion of a security-privacy trade-off. We further study the consistency and reveal a more holistic view of the threat landscape of LDP in the presence of data poisoning attacks. We comprehensively evaluate the attacks on three real-world datasets and report their effectiveness for achieving the target values. We also explore defense mechanisms and provide insights into the secure LDP design.
An $H_{\infty} $ LPV Design for Sampling Varying Controllers: Experimentation With a T-Inverted Pendulum

This brief deals with the adaptation of a real-time controller's sampling period to account for the available computing resource variations. The design of such controllers requires a parameter-dependent discrete-time model of the plant, where the parameter is the sampling period. A polytopic approach for linear parameter varying (LPV) systems is then developed to get an H∞ sampling period dependent controller. A reduction of the polytope size is here performed which drastically reduces the conservatism of the approach and makes easier the controller implementation. Some experimental results on a T-inverted pendulum are provided to show the efficiency of the approach.