Miracle-dz/UniFAR-FTUs huggingface dataset:
Divergent morphologies, performance, and escape behaviour in two tropical rock‐using lizards (Reptilia: Scincidae)

The present study quantified microhabitat use, morphology, performance (sprinting, climbing, clinging, and jumping), and escape behaviour of two closely related tropical rock-using lizards. Specifically, the study tested whether: (1) a flatter body and longer limbs enhance performance in rocky habitats; (2) escape behaviour supports predictions based on habitat openness; and (3) there is a trade-off between sprinting and climbing performance. Despite the occupation of generally similar rocky habitats, the habitat of Carlia scirtetis was more open and composed of larger boulders with more regular surfaces, whereas the habitat of Carlia mundivensis was composed of more undergrowth and leaf litter, consisting of smaller boulders with irregular surfaces. The longer legs, flatter body, and greater sprinting and climbing ability of C. scirtetis, supports ecomorphological predictions. By contrast to predictions based on habitat openness, C. scirtetis allowed a potential threat to approach closer and ran further to a refuge than C. mundivensis, suggesting that escape behaviour as determined by performance may be species-specific or decoupled in these two species. The increased sprint speed of C. scirtetis highlighted a performance trade-off, with climbing speed lagging behind that of sprint speed. These results suggest that subtle differences in the structural microhabitat and the degree of habitat openness may ultimately result in substantial differences in morphology, performance, and threat behaviour in closely-related lizard species.
Modelling and optimization of microbial production of hydrogen on agro-municipal wastes.

vi ACKNOWLEDGEMENTS . viii TABLE OF CONTENTS . ix LIST OF FIGURES . xiv LIST OF TABLES . xvi LIST OF ABBREVIATIONS. xvii CHAPTER 1 – General introduction . 1 1.1. The need for alternative energy . 1 1.2. Hydrogen as a potential energy source. 5 1.3. Problem statement . 7 1.4. Aims . 8 1.5. References . 9 CHAPTER 2 – Potential of using Organic Fraction of Solid Municipal Waste for fermentative biohydrogen production in South Africa . 12 2.1. Abstract. 12 2.2. Introduction . 12 2.3. The South African generated OFSMW and disposal challenges . 13 2.3. 1. The generated OFSMW. 13 2.3. 2. The challenges associated with the disposal of OFSMW . 17 2.4. Chemical composition of OFSMW . 17 2.5. Suitability of OFSMW for biohydrogen production . 18
A STUDY OF JOB SATISFACTION OF EMPLOYEES IN BRASS PART UNITS – JAMNAGAR CITY

This article presents a study on the job satisfaction of employees in brass part units. It analyses the expectation, factors of job satisfaction, motivation factors, job stress and support from family and society among employees in brass part units – Jamnagar city. Several factors which affect the job satisfaction of employees in brass part units have been investigated in detail by using 100 respondents as a sample. Data collected throw questionnaire. Various tools percentage analysis was used. The factors which were given importance by the employees in the workplace like service condition, nature of work, compensation, benefits, and relationship owners and opportunities for promotion were investigated in depth. Certain demographic variables were found to be related to the service condition, nature of work, compensation, benefits, relationship with owners and opportunities for promotion.
New and noteworthy distributional records of treefrogs (Anura) from southwestern Amazonia

We reviewed the herpetological collection of Universidade Federal do Acre and provide here a detailed list of information about new distributional records. We report for the first time in Brazil two anuran species ( Dendropsophus joannae and Scinax ictericus ) and we extend the known distribution of Dendropsophus marmoratus, Scinax pedromedinae and Teratohyla midas to Acre state. Besides, we provide the second and southernmost record on Scinax iquitorum and new distributional data of Dendropsophus salli from both Acre and Rondonia states.
Marketing de relacionamento no setor de ensino superior: a percepção dos alunos de uma faculdade da serra gaúcha

Resumo: O marketing de relacionamento pode ser visto como ferramenta importante para melhorar a relacao entre instituicoes de ensino superior e alunos. Esse estudo teve como objetivo analisar a percepcao do nivel de relacionamento dos alunos com uma faculdade do Rio Grande do Sul. Para tanto foi utilizada a a abordagem quantitativa com a adaptacao e revalidacao da escala de Wilson e Vlosky (1997). Os resultados indicaram uma percepcao razoavel do relacionamento. Como ponto positivo as dimensoes que obtiveram maior media foram as mencionadas por Morgan e Hunt (1994) como sendo chave para construcao e manutencao de relacionamentos duradouros, sendo elas: comprometimento e confianca. Os itens da escala de Wilson e Vlosky (1997) que mais influenciaram na avaliacao do relacionamento dizem respeito ao esforco e investimento aplicado para o relacionamento, seguido pela percepcao de parceria com a instituicao e expectativa de relacionamento por longo tempo.
Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation

Despite increasing instances of machine translation (MT) systems including contextual information, the evidence for translation quality improvement is sparse, especially for discourse phenomena. Popular metrics like BLEU are not expressive or sensitive enough to capture quality improvements or drops that are minor in size but significant in perception. We introduce the first of their kind MT benchmark datasets that aim to track and hail improvements across four main discourse phenomena: anaphora, lexical consistency, coherence and readability, and discourse connective translation. We also introduce evaluation methods for these tasks, and evaluate several baseline MT systems on the curated datasets. Surprisingly, we find that existing context-aware models do not improve discourse-related translations consistently across languages and phenomena.
Exceptional Encouraged Results in the Characterisation and Applications of Semiconducting Ceo2 and Its Dopant Nanocomposites-A Review

Cerium oxide has been widely investigated because of its multiple applications, such as a catalyst, an electrolyte material of solid oxide fuel cells, a material of high refractive index, Promising results have been obtained using cerium (Ce) oxide nanoparticles (CNPs) as antioxidants in biological systems. Oxide materials, its properties and applications were discussed. Most of the transparent conducting oxides have electrical and optical properties. Many applications were reported by these oxide semiconducting materials.
WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context

We present WiC-TSV, a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically, we introduce a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as binary classification task thus being independent of external sense inventories, and the coverage of various domains. This makes the dataset highly flexible for the evaluation of a diverse set of models and systems in and across domains. WiC-TSV provides three different evaluation settings, depending on the input signals provided to the model. We set baseline performance on the dataset using state-of-the-art language models. Experimental results show that even though these models can perform decently on the task, there remains a gap between machine and human performance, especially in out-of-domain settings. WiC-TSV data is available at https://competitions.codalab. org/competitions/23683.
Sparse Hashing for Scalable Approximate Model Counting: Theory and Practice

Given a CNF formula F on n variables, the problem of model counting, also referred to as #SAT, is to compute the number of models or satisfying assignments of F. Recent years have witnessed a surge of effort towards developing efficient algorithmic techniques that combine the classical strongly 2-universal hash functions (from [Stockmeyer 1983]) with the remarkable progress in SAT solving over the past decade. These techniques augment the CNF formula F with random XOR constraints and invoke an NP oracle repeatedly on the resultant CNF-XOR formulas. In practice, the NP oracle calls are replaced by calls to a SAT solver and it is observed that runtime performance of modern SAT solvers (based on conflict-driven clause learning) on CNF-XOR formulas is adversely affected by the size of XOR constraints. The standard construction of 2-universal hash functions chooses every variable with probability p = 1/2 leading to XOR constraints of size n/2 in expectation. Consequently, the main challenge is to design sparse hash functions, where variables can be chosen with smaller probability and lead to smaller sized XOR constraints, which can then replace strongly 2-universal hash functions. In this paper, our goal is to address this challenge both from a theoretical and a practical perspective. First, we formalize a relaxation of universal hashing, called concentrated hashing, a notion implicit in prior works to design sparse hash functions. We then establish a novel and beautiful connection between concentration measures of these hash functions and isoperimetric inequalities on boolean hypercubes. This allows us to obtain tight bounds on variance as well as the dispersion index and show that p = O(log2 m/m) suffices for the design of sparse hash functions from {0, 1}n to {0, 1}m belonging to the concentrated hash family. Finally, we use sparse hash functions belonging to this concentrated hash family to develop new approximate counting algorithms. A comprehensive experimental evaluation of our algorithm on 1893 benchmarks demonstrates that the usage of sparse hash functions can lead to significant speedups. To the best of our knowledge, this work is the first study to demonstrate runtime improvement of approximate model counting algorithms through the usage of sparse hash functions, while still retaining strong theoretical guarantees (à la 2-universal hash functions).
Distributional Soft Actor Critic for Risk Sensitive Learning

Most of reinforcement learning (RL) algorithms aim at maximizing the expectation of accumulated discounted returns. Since the accumulated discounted return is a random variable, its distribution includes more information than its expectation. Meanwhile, entropy of policy indicates its diversity and it can help improve the exploration capability of algorithms. In this paper, we present a new RL algorithm named Distributional Soft Actor Critic (DSAC), combining distributional RL and maximum entropy RL together. Taking the randomness both in action and discounted return into consideration, DSAC over performs the state-of-the-art baselines with more stability in several continuous control benchmarks. Moreover, distributional information of returns can also be used to measure metrics other than expectation, such as risk-related metrics. With a fully parameterized quantile function, DSAC is easily adopted to optimize policy under different risk preferences. Our experiments demonstrate that with distribution modeling in RL the agent performs better both for risk-averse and risk-seeking control tasks.
Cytotoxic, mutagenic and carcinogenic properties of ultraviolet radiation : shining light on photolesions

textabstractExposure to ultraviolet light (UV light) poses a serieus threat to human health. An altered life style (holidays in the sun, tanning devices) has led to increased exposure to UV light in the Western population. UV light damages the DNA, the carrier of genetic information, which can result in permanent alterations in the genome and, ultimately, cancer. The majority of the DNA lesions induced by UV light consists of cyclobutane pyrimidine dimers (CPDs) and pyrimidine-(6,4)-pyrimidone photoproducts (6-4PPs). The relative contribution of these CPDs and 6-4PPs to the effects of acute and chronic UV exposure, however, is nat known (e.g. sunburn, cancer). Although organisms are equipped with the nucleotide excision repair (NER) mechanism for remaval of lesions, this mechanism may nat offer sufficient proteetion in cases of excessive exposure to UV light. The aim of this thesis is to further elucidate the mechanisms behind the detrimental effects of UV exposure and to determine the role of individual classes of UV-induced DNA lesions in these processes. To this end, we generated mice transgenically expressing photolyase enzymes. This approach enables light-controlled remaval of a single type of lesion, allowing investigation of the contribution of individual lesions to UV responses. In Chapter 1, we review the current knowledge on UV-induced DNA damage and repair, and the consequences of UV exposure on human health. Chapters 2 and 3 describe the generation of ubiquitously expressing CPD and 6-4PP photolyase transgenie mice. We show that these marsupial and plant photolyase gene products are functional in mice, resulting in light-dependent remaval of DNA lesions from mouse skin. Furthermore, we provide evidence that CPDs are responsible for adverse UV effects including cell death, sunburn and permanent genomic alterations (mutations). In Chapter 4 we describe the generation of transgenie mice expressing photolyase from the keratinocyte-specific K14 promoter, allowing fast remaval of DNA damage by photoreactivation in basal keratinocytes of the epidermis, whereas in other cell types such as fibroblasts and Langerhans cells lesions are repaired in slow fashion (if at all). This gave us the unique opportunity to dissect the cell types involved in UV responses. In Chapter 5 the carcinogenic potential of DNA lesions are studied. Importantly, we show that remaval of CPDs alone is sufficient to delay the induction of skin cancer to a great extent. An important role in UV-induced skin carcinogenesis is performed by the immune system. We show that CPD remaval not only protects the animal from cancer by lowering the mutation laad, but it also abclishes UV-induced immunosuppression, allowing the immune system to respond adequately to malignancies. The results described in this thesis are reviewed in a general discussion in Chapter 6.
Exploring Contextualized Neural Language Models for Temporal Dependency Parsing

Extracting temporal relations between events and time expressions has many applications such as constructing event timelines and time-related question answering. It is a challenging problem that requires syntactic and semantic information at sentence or discourse levels, which may be captured by deep language models such as BERT (Devlin et al., 2019). In this paper, we developed several variants of BERT-based temporal dependency parser, and show that BERT significantly improves temporal dependency parsing (Zhang and Xue,2018a). Source code and trained models will be made available at this http URL.
Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network

Salient object detection has achieved great improvements by using the Fully Convolutional Networks (FCNs). However, the FCN-based U-shape architecture may cause dilution problems in the high-level semantic information during the up-sample operations in the top-down pathway. Thus, it can weaken the ability of salient object localization and produce degraded boundaries. To this end, in order to overcome this limitation, we propose a novel pyramid self-attention module (PSAM) and the adoption of an independent feature-complementing strategy. In PSAM, self-attention layers are equipped after multi-scale pyramid features to capture richer high-level features and bring larger receptive fields to the model. In addition, a channel-wise attention module is also employed to reduce the redundant features of the FPN and provide refined results. Experimental analysis demonstrates that the proposed PSAM effectively contributes to the whole model so that it outperforms state-of-the-art results over five challenging datasets. Finally, quantitative results show that PSAM generates accurate predictions and integral salient maps, which can provide further help to other computer vision tasks, such as object detection and semantic segmentation.
A Call for More Rigor in Unsupervised Cross-lingual Learning

We review motivations, definition, approaches, and methodology for unsupervised cross-lingual learning and call for a more rigorous position in each of them. An existing rationale for such research is based on the lack of parallel data for many of the world’s languages. However, we argue that a scenario without any parallel data and abundant monolingual data is unrealistic in practice. We also discuss different training signals that have been used in previous work, which depart from the pure unsupervised setting. We then describe common methodological issues in tuning and evaluation of unsupervised cross-lingual models and present best practices. Finally, we provide a unified outlook for different types of research in this area (i.e., cross-lingual word embeddings, deep multilingual pretraining, and unsupervised machine translation) and argue for comparable evaluation of these models.
A survey on time-sensitive resource allocation in the cloud continuum

Abstract Artificial Intelligence (AI) and Internet of Things (IoT) applications are rapidly growing in today’s world where they are continuously connected to the internet and process, store and exchange information among the devices and the environment. The cloud and edge platform is very crucial to these applications due to their inherent compute-intensive and resource-constrained nature. One of the foremost challenges in cloud and edge resource allocation is the efficient management of computation and communication resources to meet the performance and latency guarantees of the applications. Numerous research studies have been carried out to address this intricate problem. In this paper, the current state-of-the-art resource allocation techniques for the cloud continuum, in particular those that consider time-sensitive applications, are reviewed. Furthermore, we present the key challenges in the resource allocation problem for the cloud continuum, a taxonomy to classify the existing literature and the potential research gaps.
Lexical Semantic Recognition

In lexical semantics, full-sentence segmentation and segment labeling of various phenomena are generally treated separately, despite their interdependence. We hypothesize that a unified lexical semantic recognition task is an effective way to encapsulate previously disparate styles of annotation, including multiword expression identification / classification and supersense tagging. Using the STREUSLE corpus, we train a neural CRF sequence tagger and evaluate its performance along various axes of annotation. As the label set generalizes that of previous tasks (PARSEME, DiMSUM), we additionally evaluate how well the model generalizes to those test sets, finding that it approaches or surpasses existing models despite training only on STREUSLE. Our work also establishes baseline models and evaluation metrics for integrated and accurate modeling of lexical semantics, facilitating future work in this area.
Heavy Metals in Pig Livers; A Case of Munyaka Estate-Uasin-Gishu County, Kenya

have lead to alteration of their natural geochemical and biochemical cycle and balance. The risk of heavy metal contamination in meat/pork is of public health concern for both food safety and human health. The study aimed at determining the levels of lead, cadmium and mercury in pigs reared in two husbandry systems in Uasin-Gishu County, Kenya. A comparative cross-sectional study was employed. Thirty two pigs representing close to a thousand pigs in Munyaka estate were studied under two husbandry systems. Four branded manufactured feeds and 6 forage plants were analyzed by AAS machine for lead, cadmium and mercury. Results were summarized using means. The mean levels of lead, cadmium and mercury among intensively produced pigs were 0.10±0.04, 0.13±0.04 and 0.12±0.04mg/kg.wet weight respectively. The mean levels of lead, cadmiu and mercury in extensively produced pigs were 0.09±0.03, 0.18±0.05 and 0.14±0.09mg/kg.wet weight respectively. There was a significant difference (p<0.05) in cadmium levels in pigs under intensive and extensive husbandry system with extensively produced pigs having higher levels. Manufactured feed B had mean Pb levels of 0.26±0.01mg/kg.dry weight while feed D had Pb levels of 0.38±0.02mg/kg.dry weight. Cabbage leaves had mean Pb levels of 0.60±0.26 mg/kg.dry weight whereas grass on the roadside had mean Hg levels of 0.03±0.02mg/kg.dry weight with banana peelings also having mean Hg levels of 0.03±0.04mg/kg.dry weight. There was a significant difference (p<0.05) in cadmium levels in pigs under intensive and extensive husbandry systems with extensively produced pigs having higher levels. The study showed that pig livers under the study were not safe for human consumption due to the presence of mercury levels above the WHO maximum recommended levels. These metals are known to cause adverse health effects including neurological and renal disturbances neurological and renal disturbances. The Government shoul strictly enforce The Animal Diseases Act; Cap364 on prohibition of extensive husbandry system. Kenya bureau of standards (KEBS) and Department of Veterinary Services (DVS) should regularly monitor and evaluate pork to safeguard human health. Farmers should be educated on the need to discriminately use of Phosphatic fertilizers and pesticides as they contribute to HMs in the soil and the consequent uptake by plants.
Substituicao do milho por palma forrageira: comportamento ingestivo de vacas mesticas em lactacao

Replacement of the corn by forage cactus: Ingestive behavior of crossbreed lactating cows. The aim of this work was to evaluate the effects of replacement of corn by forage cactus on the ingestive behavior of eight crossbreed cows, assigned to a two 4 x 4 Latin square design. The treatments were a factorial 2 x 2 arrangement (two cultivars of forage cactus and two corn levels, with and without). There wasn't interaction between forage cactus and corn (p> 0,05). The cows that consumed giant forage cactus spent more time eating and those that consumed small forage cactus spent more time resting (p<0,01). The intake of water was lower for the animals that consumed diets with giant forage cactus and without corn (p<0,01).
Odd fracton theories, proximate orders, and parton constructions

The Lieb-Schultz-Mattis (LSM) theorem implies that gapped phases of matter must satisfy non-trivial conditions on their low-energy properties when a combination of lattice translation and $U(1)$ symmetry are imposed. We describe a framework to characterize the action of symmetry on fractons and other sub-dimensional fractional excitations, and use this together with the LSM theorem to establish that X-cube fracton order can occur only at integer or half-odd-integer filling. Using explicit parton constructions, we demonstrate that "odd" versions of X-cube fracton order can occur in systems at half-odd-integer filling, generalizing the notion of odd $Z_2$ gauge theory to the fracton setting. At half-odd-integer filling, exiting the X-cube phase by condensing fractional quasiparticles leads to symmetry-breaking, thereby allowing us to identify a class of conventional ordered phases proximate to phases with fracton order. We leverage a dual description of one of these ordered phases to show that its topological defects naturally have restricted mobility. Condensing pairs of these defects then leads to a fracton phase, whose excitations inherit these mobility restrictions.