Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding bugs in database systems via query partitioning

Logic bugs in Database Management Systems (DBMSs) are bugs that cause an incorrect result for a given query, for example, by omitting a row that should be fetched. These bugs are critical, since they are likely to go unnoticed by users. We propose Query Partitioning, a general and effective approach for finding logic bugs in DBMSs. The core idea of Query Partitioning is to, starting from a given original query, derive multiple, more complex queries (called partitioning queries), each of which computes a partition of the result. The individual partitions are then composed to compute a result set that must be equivalent to the original query's result set. A bug in the DBMS is detected when these result sets differ. Our intuition is that due to the increased complexity, the partitioning queries are more likely to stress the DBMS and trigger a logic bug than the original query. As a concrete instance of a partitioning strategy, we propose Ternary Logic Partitioning (TLP), which is based on the observation that a boolean predicate p can either evaluate to TRUE, FALSE, or NULL. Accordingly, a query can be decomposed into three partitioning queries, each of which computes its result on rows or intermediate results for which p, NOT p, and p IS NULL hold. This technique is versatile, and can be used to test WHERE, GROUP BY, as well as HAVING clauses, aggregate functions, and DISTINCT queries. As part of an extensive testing campaign, we found 175 bugs in widely-used DBMSs such as MySQL, TiDB, SQLite, and CockroachDB, 125 of which have been fixed. Notably, 77 of these were logic bugs, while the remaining were error and crash bugs. We expect that the effectiveness and wide applicability of Query Partitioning will lead to its broad adoption in practice, and the formulation of additional partitioning strategies.
Efficacy testing of eco-friendly and commercial antiviral products for the management of Zucchini Yellow Mosaic Virus

An experiment was conducted to test the efficacy of eco-friendly and commercial antiviral products for the management of Zucchini yellow mosaic virus of zucchini squash at Plant Pathology Division Khumaltar, NARC. The experiment was conducted using a randomized complete block design with eight treatments namely Garlic clove extracts@ 50ml/lit, Victovirus@3ml/lit, Bougainvillea leaf extracts@200ml//lit, Viricon-H@3ml/lit, Cow–urine@200ml/lit, Anti-Vs@1gm/lit, Control and Yoghurt extracts@25ml/lit, each ANALYSIS 55(285), September, 2019 DISCOVERY ISSN 2278–5469 EISSN 2278–5450
Further observations on the use of field enclosures for the study of the wild rabbit, Oryctolagus cuniculus (L.)

Populations of wild rabbits, Oryctolagus cuniculus (L.), can be managed experimentally in 2-acre enclosures, providing the pregnant females are allowed to dig a short burrow in which the young are born. Nestlings should not be handled within a day of birth, since this usually leads to desertion by the parent. A method of finding and examining the nesting chamber is described. Drowning causes large mortalities amongst nestlings, on flat sites, after steady rain. Predators can also oause large mortalities among the young rabbits unless special precautions are taken to keep them out. Biological data collected during the experiment show that nestling rabbits increase in weight from about 36 g when 1 day old at an approximate rate of 7.4 gjday so that they weigh about 185 g when they emerge from the burrow at the age of 21 days. Other data suggest that where dry conditions oause the cessation of reproductive activity all unweaned members of the population die, and the growth rates of recently weaned rabbits are markedly retarded. General problems of technique are discussed.
Elucidating Mechanisms of Benzo[a]pyrene Mediated Apoptotic and Autophagic Cell Death and its Prevention with Phytotherapeutics

Polycyclic aromatic hydrocarbons form an active source of air pollution that affects our health and environment. In this study, we deciphered the role of benzo[a]pyrene (B[a]P) on cellular mechanism associated cell death. The particulate matter collected from an industrial area of Rourkela city found to have B[a]P and other unidentified environmental pollutants that had mutagenic and proapoptotic activity. The apoptotic potential of B[a]P was supported by ligand-protein and protein-protein interaction in silico which was validated on human keratinocyte (HaCaT) cell line. Our prediction showed that B[a]P was activated by cytochrome P450 (CYP1B1) to induce multiple cellular effects related to activation of the aryl hydrocarbon receptor (AhR) due to formation of toxic metabolites and this in turn activated caspases. Further, we showed that B[a]P induced mitochondrial mediated autophagy dependent cell death through the canonical pathway in HaCaT cells. The autophagic cell death induced by B[a]P was found to be mediated through AMPK/mTOR pathway. We showed that B[a]P abrogated ATP generation and activated reactive oxygen production to induce toxic mitophagy in HaCaT cells. In addition, we identified Bacopa monneiri (BM) plant extract as an inducer of protective autophagy, which may directly contribute to the antioxidant promoting potential of BM on B[a]P induced cell death through Beclin-1 dependent autophagy activation. The present study provided deep insight into the mechanism of B[a]P-mediated cellular toxicity and elucidated the further scope for the development of phytotherapeutics against environmental air pollutants.
Antimicrobial-resistant Salmonella spp. isolated from retail farmed shrimp in Kuala Lumpur

Antimicrobial resistant Salmonella is recognized as a potential food safety threat and its prevalence in farmed shrimps is very concerning. However, information about antimicrobial resistant Salmonella in retail farmed shrimps in Malaysia is very limited. Therefore, this study was aimed at determining the level of Salmonella contamination of farmed shrimps at selected retails in Kuala Lumpur and antibiotic resistance pattern of Salmonella isolated from retail farmed shrimps. Farmed shrimp samples were collected from selected hypermarkets and indoor markets. Salmonella was detected by conventional methods. All presumptive colonies of Salmonella were subjected to antimicrobial susceptibility test. A high rate of Salmonella contamination was detected (n = 9, 60%) with an estimated Salmonella load ranging between 0 and >800 x 108 cfu/ml. All isolates (100%) were resistant to at least one antimicrobial agent, and 17 isolates (94.4%) were multidrug-resistant. 2 isolates (11.1%) were resistant to all eight types of antimicrobial agents. High rates of resistance were observed for erythromycin (100%), doxycycline (77.8%), tetracycline (72.2%), nalidixic acid (61.1%), ampicillin (55.6%) and chloramphenicol (44.4%). Findings from the present study provide insight on antibiotic resistant Salmonella contamination in retail farmed shrimps and suggest its potential food safety risk to the public. These data are valuable to warrant further investigation of risk management and public health strategies.
StitchNet: Image Stitching using Autoencoders and Deep Convolutional Neural Networks

This thesis explores the prospect of artificial neural networks for image processing tasks. More specifically, it aims to achieve the goal of stitching multiple overlapping images to form a bigger, panoramic picture. Until now, this task is solely approached with ”classical”, hardcoded algorithms while deep learning is at most used for specific subtasks. This thesis introduces a novel end-to-end neural network approach to image stitching called StitchNet, which uses a pretrained autoencoder and deep convolutional networks. Additionally to presenting several new datasets for the task of supervised image stitching with each 120’000 training and 5’000 validation samples, this thesis also conducts various experiments with different kinds of existing networks designed for image superresolution and image segmentation adapted to the task of image stitching. StitchNet outperforms most of the adapted networks in both quantitative as well as qualitative results.
Advanced Time Imaging

Time imaging methods are important and widely used in industry and academia. A first guess of a subsurface image can be achieved quickly with time migration. There are several different techniques which aim to improve the migration result. In this work, I consider two techniques in more detail, migration denoising and migration velocity analysis (MVA). I introduce a loop of migration and the inverse process, demigration. These methods are based on the implicit common-reflection surface (CRS) operator and provide the basis for the denoising and MVA. The reduction of the noise content in seismic data has been performed for a long a time. I investigate three different methods, which partly build on each other, to increase the signal-to-noise ratio (SNR) of the data. The application of the migration/demigration loop leads to a first noise reduction. This process is used as input for the migration deconvolution and the deep convolutional neuronal network. All methods suppress different kinds of noise in the data. The introduced MVA is a two step process. First a velocity model is automatically calculated using the kinematic wavefield attributes, which are available after a multi-parameter stack. The second step includes the MVA with a refinement of the velocities. I suggest using the coherence section of the migrated image as a mask to identify prominent reflections and weaker diffractions with higher coherence values. These areas are linked by a subsequent interpolation and smoothing. All presented methods are applied to a field data set including salt diapirs and complex subsurface structures. The denoising methods and the MVA significantly improve the migrated image, especially in the salt area and nearby regions. In addition, some techniques are extended to 3D to process challenging 3D P-cable data. The characteristic of this special kind of acquisition are short source-receiver offsets and a high frequency source. This leads to an increased resolution and makes conventional velocity-model building practically impossible without additional information. I suggest a method based on diffraction processing to obtain velocities suitable for time migration. Diffractions are energy that was scattered in all directions by small-scale objects. This property can be used as a tool for the suggested velocity-model building even for short, source-receiver offsets. This procedure is the first consistent approach that leads to a 3D time-migrated image of P-cable data.
Gear fault detection using Wavelet Transformation Method/Morlet Wavelet

Detection of machine component failure is very important to be properly applied in a maintenance program in industries. The objective of this research is to detect gear fault based on an acoustic emission signal. The signal generated by a pairs of gear rotated at 1200 RPM. A spur gear with 28 teeth is employed. Continuous Wavelet Transforms (CWT) is used to obtain time-frequency signal representation (scalogram). Furthermore gear fault detection is performed by observing pattern in scalogram. Unlike gear fault detection based on high or low amplitudes of gear mesh frequency corresponding to severity of gear fault, scalogram shows spatial data pattern correspond to the severity of gear fault. In addition, the severity level (gear with 25%, 50%, 75% and 100% tooth-cut) is able to be detected qualitatively. The results have showed that CWT is able to detect gear fault and the corresponding severity level so that it can be a complement of condition based maintenance program based on vibration signal. Abstrak. Deteksi kegagalan komponen mesin sangat penting dilakukan dengan tepat dalam program perawatan mesin di industri. Penelitian ini bermaksud untuk mendeteksi kerusakan roda gigi berdasarkan sinyal emisi akustik. Sinyal emisi akustik berasal dari struktur 2 buah roda gigi lurus yang bertautan yang diputar pada kecepatan konstan 1200 rpm. Tiap roda gigi mempunyai 28 gigi. Continuous Wavelet Transform (CWT) digunakan untuk menampilkan sinyal dalam domain waktu-frekuensi. Selanjutnya deteksi kerusakan roda gigi dilakukan dengan mengamati pola-pola yang ditampilkan oleh scalogram. Tidak seperti pada deteksi kerusakan gigi roda gigi berdasarkan signature getaran yang menampilkan frekuensi gearmesh dan amplitudo yang rendah atau tinggi sesuai dengan tingkat kerusakan, pola pada scalogram memungkinkan untuk mengamati data spatial ketika frekuensi yang berkaitan dengan kerusakan terjadi. Selain itu besarnya tingkatan kerusakan (gigi roda gigi patah 25%, 50%, 75% dan 100%) juga dapat dideteksi secara kualitatif. Hasil penelitian telah menunjukkan bahwa CWT dapat digunakan untuk deteksi kerusakan roda gigi dan tingkatan kerusakannya sehingga dapat digunakan untuk melengkapi kegiatan perawatan berbasis kondisi (condition based maintenance) yang menggunakan data getaran mesin. Kata kunci: CWT, emisi akustik (EA), scalogram, roda gigi © 2017. BKSTM-Indonesia. All rights reserved
A VIBRATION HARVESTING SYSTEM FOR BRIDGE HEALTH MONITORING APPLICATIONS

This paper presents the design, fabrication, and testing of an electromagnetic inertial micro power generation system for scavenging the very low-amplitude, low-frequency, and non-periodic vibrations present on bridges. The fabricated device can generate a peak power of 57μW and an average power of 2. 3μW from an input acceleration of 0.54m/s 2 at only 2Hz. The generator is capable of operating over an unprecedentedly large acceleration (0.54-9.8m/s 2 ) and frequency range (up to 30Hz) without any modifications or tuning. Scavenging energy from arbitrary vibrations is demonstrated using an acceleration recording from a highway overpass bridge.
REVIEW: New information on the protein requirements and diet formulation for dairy calves and heifers since the Dairy NRC 20011

ABSTRACT Research published since publication of the 2001 NRC publication Nutrient Requirements for Dairy Cattle relating to protein needs of calves and heifers was reviewed and compared with requirements from NRC (2001). Experiments used varied intakes or concentrations of CP or varied fractions of CP in the diet relative to energy. Animal requirements were reviewed in 4 categories to identify advances in understanding of nutritional requirements since publication of NRC (2001). Categories included 1) preweaned calves less than 2 mo of age fed milk or milk replacer and starter, 2) calves transitioning through weaning to approximately 4 mo of age fed starter with limited forage, 3) heifers from 4 mo to breeding, and 4) postbreeding age heifers. For calves in category 1, new data estimating optimal ratios of amino acids were identified. For calves in categories 1 and 2, new data estimating optimum ratios of CP to ME were identified but were limited. For heifers in category 3, optimum diet CP:ME appeared similar to NRC (2001). There were no experiments that tested the 70% RDP of CP recommendation for calves in category 3; however, approximately 65% RDP supported more typical dairy heifer ADG than did lower amounts. Few differences from NRC (2001) were found for heifers in category 4. Precision or limit feeding versus more conventional ad libitum feeding programs appears to offer utility to save costs and reduce nutrient and fecal outputs with dietary adjustments to maintain protein intake relative to energy and DMI.
Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control

Deep Reinforcement Learning (Deep RL) has been receiving increasingly more attention thanks to its encouraging performance on a variety of control tasks. Yet, conventional regularization techniques in training neural networks (e.g., $L_2$ regularization, dropout) have been largely ignored in RL methods, possibly because agents are typically trained and evaluated in the same environment, and because the deep RL community focuses more on high-level algorithm designs. In this work, we present the first comprehensive study of regularization techniques with multiple policy optimization algorithms on continuous control tasks. Interestingly, we find conventional regularization techniques on the policy networks can often bring large improvement, especially on harder tasks. We also compare these techniques with the more widely used entropy regularization. Our findings are shown to be robust against training hyperparameter variations. In addition, we study regularizing different components and find that only regularizing the policy network is typically the best. Finally, we discuss and analyze why regularization may help generalization in RL from four perspectives: sample complexity, reward distribution, weight norm, and noise robustness. We hope our study provides guidance for future practices in regularizing policy optimization algorithms. Our code is available at https://github.com/xuanlinli17/po-rl-regularization .
Molecular detection of Eastern Equine Encephalitis virus in mosquitoes from La Pintada (Antioquia)

Objetivo. La deteccion de arbovirus emergentes y re-emergentes a partir de mosquitos provenientes de areas semi-urbanas y rurales es fundamental para predecir posibles eventos epidemicos en poblaciones humanas. En el municipio de La Pintada (Departamento de Antioquia), caracterizado por la presencia de remanentes de bosque seco tropical, actividades de pesca, turismo, explotacion agropecuaria y minera, se realizo un estudio entomologico para explorar la posible presencia y circulacion de arbovirus de importancia en salud publica. Materiales y Metodos. Los mosquitos adultos fueron recolectados en sitios urbanos y rurales en febrero-abril del ano 2012. Los especimenes colectados fueron almacenados en tanques de nitrogeno liquido, y luego separados en grupos utilizando claves taxonomicas para genero. Para la deteccion de los virus se realizo extraccion de RNA y RT-PCR generica/anidada para los generos Flavivirus, Alphavirus, Orthobunyavirus (Grupo Bunyamwera) y Phlebovirus. Resultados. 1274 mosquitos adultos e inmaduros fueron colectados, pertenecientes en su mayoria a los generos Culex y Aedes. Los extractos de RNA de 64 pools fueron evaluados por RT-PCR. Se encontro un pool positivo para Alphavirus. La secuenciacion de los productos de RT-PCR y el analisis con secuencias depositadas en GenBank indica la presencia del virus de Encefalitis Equina del Este (EEEV). Conclusiones. Este es el primer registro de infeccion natural del virus de encefalitis equina del este (EEEV) en mosquitos de La Pintada (Antioquia, Colombia), un area con factores ecologicos aptos para la emergencia y re-emergencia de arbovirus de importancia veterinaria y medica.
Seasonal Changes in Feeding Pressures of Fruit- and Nectar-Eating Birds in Panama

It is only recently that the seasonal fluctuations of fruit and nectar abundance have become well documented in the botanical literature for the New World tropics (Janzen 1967; Croat 1969). Much work now remains for the zoologists, however, to correlate these fluctuations with the seasonal aspects of the life histories of animals. In this study, the feeding behavior and ecology of fruitand nectareating birds were examined in the Panama Canal Zone to determine how they were affected by seasonal changes of food supply.
Slice-Aware Neural Ranking

Understanding when and why neural ranking models fail for an IR task via error analysis is an important part of the research cycle. Here we focus on the challenges of (i) identifying categories of difficult instances (a pair of question and response candidates) for which a neural ranker is ineffective and (ii) improving neural ranking for such instances. To address both challenges we resort to slice-based learning for which the goal is to improve effectiveness of neural models for slices (subsets) of data. We address challenge (i) by proposing different slicing functions (SFs) that select slices of the dataset—based on prior work we heuristically capture different failures of neural rankers. Then, for challenge (ii) we adapt a neural ranking model to learn slice-aware representations, i.e. the adapted model learns to represent the question and responses differently based on the model’s prediction of which slices they belong to. Our experimental results (the source code and data are available at https://github.com/Guzpenha/slice_based_learning) across three different ranking tasks and four corpora show that slice-based learning improves the effectiveness by an average of 2% over a neural ranker that is not slice-aware.
Larval Honey Bee Response to Various Doses of Bacillus larvae Spores

Larvae from 4 sister queens of Apis mellifera L, from each of 2 genetically different lines of honey bees, 1 susceptible and 1 resistant, were subjected in 2 trials to 7 dosage levels of spores of Bacillus larvae White. Doses applied were 0, 20, 70, 130, 950, 11,000, and 114,000 spores in 0.287 mm3 of distilled water placed individually in the larval food. Larvae 0–6, 18–24, and 36–42 hours old were used to test effect of the spore levels on different ages. In the 0–6 hour age group, the median lethal dosage and slopes of the 2 lines were nearly the same. The susceptible line had an LD50 of 275 spores and a slope of 0.826 compared with an LD50 of 187 spores and a slope of 0.835 for the resistant line. There was a threshold below which larval mortality did not exceed the check, while any dose above 950 spores gave greater than 80% mortality. At 18–24 hours, the LD50’s were 2500 and 1300 spores, while the slopes were 0.496 and 0.663 for the resistant and susceptible lines, respectively. The resistant line had developed resistance much earlier, as is evidenced by the LD50 and slope. The 36 to 42-hour age group had attained sufficient resistance to resist infection at all dosage levels, and no LD50 or slope could be ascertained. Neither line greatly exceeded the 10% mortality level at any spore concentration applied at this age. The conclusion was that dosage-mortality relationships in the Bacillus larvae -honey bee system are greatly influenced by larval age and genetic constitution.
Hiding the Access Pattern is Not Enough: Exploiting Search Pattern Leakage in Searchable Encryption

Recent Searchable Symmetric Encryption (SSE) schemes enable secure searching over an encrypted database stored in a server while limiting the information leaked to the server. These schemes focus on hiding the access pattern, which refers to the set of documents that match the client's queries. This provides protection against current attacks that largely depend on this leakage to succeed. However, most SSE constructions also leak whether or not two queries aim for the same keyword, also called the search pattern. In this work, we show that search pattern leakage can severely undermine current SSE defenses. We propose an attack that leverages both access and search pattern leakage, as well as some background and query distribution information, to recover the keywords of the queries performed by the client. Our attack follows a maximum likelihood estimation approach, and is easy to adapt against SSE defenses that obfuscate the access pattern. We empirically show that our attack is efficient, it outperforms other proposed attacks, and it completely thwarts two out of the three defenses we evaluate it against, even when these defenses are set to high privacy regimes. These findings highlight that hiding the search pattern, a feature that most constructions are lacking, is key towards providing practical privacy guarantees in SSE.