Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronous Voice Applied Customer Access based on IEEE 802.11

The analysis of infrastructure IEEE 802.11 protocol based wireless access network with point coordination (PCF) for synchronized voice and reliable quality data transmission is presented. It is shown, that it is possible to create wireless customer access with wired network quality by synchronizing voice source coders with beacon periods. The analysis of this system has been validated by simulations in Opnet. The modeling additionally evaluates wireless channel capacity in terms of provided voice channels while keeping reasonable packet loss. The defined capacity is greater than capacity evaluations presented in other publications. Ill. 7, bibl. 11 (in English; summaries in English, Russian and Lithuanian).
Handbook of Enology

THE CHEMISTRY OF WINE. Organic Acids in Wine. Alcohols and Other Volatile Compounds. Carbohydrates. Dry Extract and Minerals. Nitrogen Compounds. Phenolic Compounds. Varietal Aroma. STABILIZATION AND TREATMENTS OF WINE. Chemical Nature, Origins and Consequences of the Main Organoleptic Defects. The Concept of Clarity and Colloidal Phenomena. Clarification and Stabilization Treatments: Fining Wine. Clarifying Wine by Filtration and Centrifugation. Stabilizing Wine by Physical and Physicochemical Processes. Aging Red Wines in Vat and Barrel: Phenomena Occurring During Aging. Index.
Job creation abroad and worker retention at home

Using linked data on German manufacturing employees and their employers’ multinational activities, we document that multinational enterprises (MNEs) exhibit four percent smaller rates of job loss than non-MNEs. The higher retention rates at MNEs cannot be explained by a comprehensive set of present or past employee, employer and sector characteristics alone. A significant part of the higher worker retention rates at MNEs is either due to the MNE’s foreign expansion itself or to the employer’s inherent competitive success across locations. Significantly higher worker retention rates at MNEs are consistent with the notion that hindering MNEs in their foreign expansions would result in even more domestic job losses to globalization.
Influence of initial spacing on the stem shape of Pinus taeda L. trees

The objective of this study was to analyze the effect of spacing on the stem shape of Pinus taeda L. trees. Data from a spacing experiment carried out at the company IGARAS, in Santa Catarina, Brazil, were used for this purpose. The analyzed spacings were: 1.5 x 1.0 m; 2.0 x 1.0 m; 2.5 x 1.0 m; 1.5 x 2.0 m; 2.0 x 2.0 m; 1.5 x 3.0 m; 2.5 x 2.0 m; 2.0 x 3.0 m; and 2.5 x 3.0 m. The taper models tested were those proposed by Demaerschalk, Garay and Biging, with the model of Garay being selected. Through model identity tests, it was verified that the smallest spacings resulted in less conical shape than the largest ones.
Mycorrhizal efficacy of trifoliate orange seedlings on alleviating temperature stress

Citrus plants often suffer from temperature stress, which seriously inhibits tree growth and even results in tree death. The present experiment was conducted to evaluate the effects of Glomus mosseae on growth, root morphology, superoxide dismutase (SOD) and catalase (CAT) activities, and soluble protein content of trifoliate orange (Poncirus trifoliata) seedlings at low (15°C), optimum (25°C) and high (35°C) temperatures. Sixty-eight days after temperature stresses, mycorrhizal colonization and number of both entry points and vesicles were significantly inhibited by low or high temperature. Mycorrhizal seedlings recorded significantly higher growth characteristics than non-mycorrhizal seedlings at both optimum and high temperatures, but the beneficial effects were almost lost at low temperature. Generally, mycorrhizal seedlings presented notably higher root traits (projected area, surface area, number of forks and volume) than non-mycorrhizal seedlings regardless of temperature levels. Mycorrhizal colonization significantly increased SOD and CAT activities and soluble protein content at high temperature, in creased only SOD activity at optimum temperature, and decreased only soluble protein content at low temperature. It suggests that mycorrhizal alleviation of temperature stress in trifoliate orange seedlings was at high temperature, but the alleviation was obviously weakened at low temperature.
Study of nonlinear effects of intense UV beams in the atmosphere

Les faisceaux lasers de hautes puissances declenchent durant leur propagation la formation d’effets nonlineaires. Si l’intensite est suffisamment elevee l’accumulation de ces effets peut provoquer un mode de propagation s’approchant des caracteristiques des guides d’ondes. Ce phenomene est appele filamentation. Il est amplement complexe et extensivement etudie pour les faisceaux IR mais injustement ignore pour l’UV. Dans cette these, l’etude du cas UV est traitee. Une double etude theorique pour caracteriser le profil du faisceau et sa propagation est developpee. Ensuite l’etude experimentale est realisee en commencant par la construction du laser permettant une telle etude, puis les resultats experimentaux de la filamentation UV. Les resultats theoriques et l’observation experimentales menent tous deux a l’observation de la propagation d’un faisceau UV de environ 600microns pour une duree d’impulsion de 200ps et une energie de l’ordre de 200mJ.
Collective Remittances and the State: The 3x1 Program in Mexican Municipalities

The Mexican 3x1 Program for Migrants is a matching-fund scheme that seeks to direct the money sent by hometown associations abroad (collective remittances) to productive uses. Federal, state and municipal governments contribute to the program, multiplying by three the contributions sent by migrants living abroad. Using municipal-level data on program participation for the period 2002–2007, we evaluate the program’s capacity to target the poorest municipalities. Since migration has a nonlinear relationship with poverty and marginality, a program that unconditionally responds to project initiatives from migrant organizations is bound to be regressive due to self-selection bias. Indeed, poorer municipalities are less likely to participate, and they also receive smaller amounts of money and fewer projects than richer localities. Moreover, we find evidence of a partisan bias: electoral support for the PAN is associated with more funds or projects awarded. Given that high-migration PAN strongholds are relatively well-off municipalities, geography and politics reinforce each other in producing a regressive outcome.
Impact of Long‐Term No‐Tillage and Cropping System Management on Soil Organic Carbon in an Oxisol: A Model for Sustainability

Soil organic carbon (SOC) was assessed in a long-term (19 yr) experiment comparing conventional tillage (CT) and no-tillage (NT) management systems and various winter cover crop treatments in a Rhodic Hapludox in southern Brazil. After 19 yr, NT resulted in 6.84 Mg C ha -1 , in the upper soil layer (0-10 cm), which represented 64.6% more than CT. In the 0 to 20 cm soil layer, the NT system sequestered 1.24 Mg C ha -1 yr -1 , while CT sequestered 0.96 Mg C ha -1 yr -1 . Independent of soil management, the fallow treatment resulted in the lowest SOC stocks to the 40-cm soil depth compared to all other winter treatments. We compared SOC levels of the experimental site with a nearby-forested area, which has never been cleared. No-till management combined with winter cover crops resulted in soil properties that most closely resembled the undisturbed forest. Maize grain yields and soybean seed yields were 6 and 5% higher, respectively, under NT than CT. Our results point to NT management combined with winter cover crops as the management system of choice to achieve sustainable crop production on Oxisols in the subtropical and tropical regions of the world.
Global 3‐D land‐ocean‐atmosphere model for mercury: Present‐day versus preindustrial cycles and anthropogenic enrichment factors for deposition

We develop a mechanistic representation of land‐atmosphere cycling in a global 3‐D ocean‐atmosphere model of mercury (GEOS‐Chem). The resulting land‐ocean‐atmosphere model is used to construct preindustrial and present biogeochemical cycles of mercury, to examine the legacy of past anthropogenic emissions, to map anthropogenic enrichment factors for deposition, and to attribute mercury deposition in the United States. Land emission in the model includes prompt recycling of recently deposited mercury (600 Mg a−1 for present day), soil volatilization (550 Mg a−1), and evapotranspiration (550 Mg a−1). The spatial distribution of soil concentrations is derived from local steady state between land emission and deposition in the preindustrial simulation, augmented for the present day by a 15% increase in the soil reservoir distributed following the pattern of anthropogenic deposition. Mercury deposition and hence emission are predicted to be highest in the subtropics. Our atmospheric lifetime of mercury against deposition (0.50 year) is shorter than past estimates because of our accounting of Hg(0) dry deposition, but recycling from surface reservoirs results in an effective lifetime of 1.6 years against transfer to long‐lived reservoirs in the soil and deep ocean. Present‐day anthropogenic enrichment of mercury deposition exceeds a factor of 5 in continental source regions. We estimate that 68% of the deposition over the United States is anthropogenic, including 20% from North American emissions (20% primary and <1% recycled through surface reservoirs), 31% from emissions outside North America (22% primary and 9% recycled), and 16% from the legacy of anthropogenic mercury accumulated in soils and the deep ocean.
Detección de la enterotoxina A de Staphylococcus aureus mediante la reacción en cadena de la polimerasa (PCR) y su correlación con las pruebas de coagulasa y termonucleasa

Staphylococcus aureus is a pathogenic bacterium, widely distributed on nature and associated to general infection and food borne outbreaks. The relationship between this bacterium and food borne outbreaks has been done, historically, using several tests, including coagulase, thermonuclease and actually, PCR for the genes codifying for the enterotoxin responsible of clinical symptoms. The objective of this work is to detect enterotoxin A codifying gene through PCR in a group of S. aureus strains isolated from food samples, and also to correlate the presence of this gene with the production of coagulase and thermonuclease enzymes. A total of 69 staphylococcal strains were analyzed, 58 obtained from non pasteurized milk samples from the Estacion Experimental Alfredo Volio Mata and 11 from the Food and Water Microbiology Laboratory collection, Universidad de Costa Rica. Coagulase, thermonuclease and enterotoxin A were analyzed in all the strains, and a statistical correlation was performed in order to verify possible associations. Results show that there is no correlation between the three variables, nevertheless, all coagulase positive strains were thermonuclease positive, and all enterotoxin positive strains were coagulase and thermonuclease positive, but not inversely. These results show that the use of presumptive or indirect tests for establishing entorotoxigenity of S. aureus strains is not truthful, more sensible and specific analysis, as PCR, shall be performed.
Delayed Feedback Modeling for the Entire Space Conversion Rate Prediction

Estimating post-click conversion rate (CVR) accurately is crucial in E-commerce. However, CVR prediction usually suffers from three major challenges in practice: i) data sparsity: compared with impressions, conversion samples are often extremely scarce; ii) sample selection bias: conventional CVR models are trained with clicked impressions while making inference on the entire space of all impressions; iii) delayed feedback: many conversions can only be observed after a relatively long and random delay since clicks happened, resulting in many false negative labels during training. Previous studies mainly focus on one or two issues while ignoring the others. In this paper, we propose a novel neural network framework ESDF to tackle the above three challenges simultaneously. Unlike existing methods, ESDF models the CVR prediction from a perspective of entire space, and combines the advantage of user sequential behavior pattern and the time delay factor. Specifically, ESDF utilizes sequential behavior of user actions on the entire space with all impressions to alleviate the sample selection bias problem. By sharing the embedding parameters between CTR and CVR networks, data sparsity problem is greatly relieved. Different from conventional delayed feedback methods, ESDF does not make any special assumption about the delay distribution. We discretize the delay time by day slot and model the probability based on survival analysis with deep neural network, which is more practical and suitable for industrial situations. Extensive experiments are conducted to evaluate the effectiveness of our method. To the best of our knowledge, ESDF is the first attempt to unitedly solve the above three challenges in CVR prediction area.
Efficient Approximate Nearest Neighbor Search for Multiple Weighted lp≤2 Distance Functions

Nearest neighbor search is fundamental to a wide range of applications. Since the exact nearest neighbor search suffers from the "curse of dimensionality", approximate approaches, such as Locality-Sensitive Hashing (LSH), are widely used to trade a little query accuracy for a much higher query efficiency. In many scenarios, it is necessary to perform nearest neighbor search under multiple weighted distance functions in high-dimensional spaces. This paper considers the important problem of supporting efficient approximate nearest neighbor search for multiple weighted distance functions in high-dimensional spaces. To the best of our knowledge, prior work can only solve the problem for the $l_2$ distance. However, numerous studies have shown that the $l_p$ distance with $p\in(0,2)$ could be more effective than the $l_2$ distance in high-dimensional spaces. We propose a novel method, WLSH, to address the problem for the $l_p$ distance for $p\in(0,2]$. WLSH takes the LSH approach and can theoretically guarantee both the efficiency of processing queries and the accuracy of query results while minimizing the required total number of hash tables. We conduct extensive experiments on synthetic and real data sets, and the results show that WLSH achieves high performance in terms of query efficiency, query accuracy and space consumption.
Eppur è piatto? The Cosmic Chronometers Take on Spatial Curvature and Cosmic Concordance

The question of whether cosmic microwave background (CMB) temperature and polarization data from Planck favor a spatially closed universe with curvature parameter ΩK < 0 has been the subject of recent intense discussions. Attempts to break the geometrical degeneracy combining Planck data with external data sets such as baryon acoustic oscillation (BAO) measurements all point toward a spatially flat universe at the cost of significant tensions with Planck, which makes the resulting data set combination problematic. Settling this issue requires identifying a data set that can break the geometrical degeneracy while avoiding these tensions. We argue that cosmic chronometers (CCs), measurements of the expansion rate H(z) from the relative ages of massive early-type passively evolving galaxies, are the data set we are after. Furthermore, CCs come with the additional advantage of being virtually free of cosmological model assumptions. Combining Planck 2018 CMB temperature and polarization data with the latest CCs, we break the geometrical degeneracy and find ΩK = −0.0054 ± 0.0055, consistent with a spatially flat universe and competitive with the Planck+BAO constraint. Our results are stable against minimal parameter space extensions and CC systematics, and we find no substantial tension between Planck and CC data within a nonflat universe, making the resulting combination reliable. Our results allow us to assert with confidence that the universe is spatially flat to the level, a finding that might possibly settle the ongoing spatial curvature debate and lends even more support to the already very successful inflationary paradigm.
THE STABLE LIMIT DAHA AND THE DOUBLE DYCK PATH ALGEBRA

We study the compatibility of the action of the DAHA of type GL with two inverse systems of polynomial rings obtained from the standard Laurent polynomial representations. In both cases, the crucial analysis is that of the compatibility of the action of the Cherednik operators. Each case leads to a representation of a limit structure (the +/– stable limit DAHA) on a space of almost symmetric polynomials in infinitely many variables (the standard representation). As an application, we show that the defining representation of the double Dyck path algebra arises from the standard representation of the +stable limit DAHA.
Energy-Based Models for Continual Learning

We motivate Energy-Based Models (EBMs) as a promising model class for continual learning problems. Instead of tackling continual learning via the use of external memory, growing models, or regularization, EBMs have a natural way to support a dynamically-growing number of tasks or classes that causes less interference with previously learned information. We find that EBMs outperform the baseline methods by a large margin on several continual learning benchmarks. We also show that EBMs are adaptable to a more general continual learning setting where the data distribution changes without the notion of explicitly delineated tasks. These observations point towards EBMs as a class of models naturally inclined towards the continual learning regime.
Unravelling the origin of magnetic fields in galaxies

Despite their ubiquity, there are many open questions regarding galactic and cosmic magnetic fields. Specifically, current observational constraints cannot rule out if magnetic fields observed in galaxies were generated in the Early Universe or are of astrophysical nature. Motivated by this we use our magnetic tracers algorithm to investigate whether the signatures of primordial magnetic fields persist in galaxies throughout cosmic time. We simulate a Milky Way-like galaxy in four scenarios: magnetised solely by primordial magnetic fields, magnetised exclusively by SN-injected magnetic fields, and two combined primordial + SN magnetisation cases. We find that once primordial magnetic fields with a comoving strength $B_0 >10^{-12}$ G are considered, they remain the primary source of galaxy magnetisation. Our magnetic tracers show that, even combined with galactic sources of magnetisation, when primordial magnetic fields are strong, they source the large-scale fields in the warm metal-poor phase of the simulated galaxy. In this case, the circumgalactic and intergalactic medium can be used to probe $B_0$ without risk of pollution by magnetic fields originated in the galaxy. Furthermore, whether magnetic fields are primordial or astrophysically-sourced can be inferred by studying local gas metallicity. As a result, we predict that future state-of-the-art observational facilities of magnetic fields in galaxies will have the potential to unravel astrophysical and primordial magnetic components of our Universe.
Trial emulation and survival analysis for disease incidence registers: A case study on the causal effect of pre‐emptive kidney transplantation

When drawing causal inference from observed data, failure time outcomes present additional challenges of censoring often combined with other missing data patterns. In this article, we follow incident cases of end‐stage renal disease to examine the effect on all‐cause mortality of starting treatment with transplant, so‐called pre‐emptive kidney transplantation, vs starting with dialysis possibly followed by delayed transplantation. The question is relatively simple: which start‐off treatment is expected to bring the best survival for a target population? To address it, we emulate a target trial drawing on the long term Swedish Renal Registry, where a growing common set of baseline covariates was measured nationwide. Several lessons are learned which pertain to long term disease registers more generally. With characteristics of cases and versions of treatment evolving over time, informative censoring is already introduced in unadjusted Kaplan‐Meier curves. This leads to misrepresented survival chances in observed treatment groups. The resulting biased treatment association may be aggravated upon implementing IPW for treatment. Aware of additional challenges, we further recall how similar studies to date have selected patients into treatment groups based on events occurring post treatment initiation. Our study reveals the dramatic impact of resulting immortal time bias combined with other typical features of long‐term incident disease registers, including missing covariates during the early phases of the register. We discuss feasible ways of accommodating these features when targeting relevant estimands, and demonstrate how more than one causal question can be answered relying on the no unmeasured baseline confounders assumption.
InstaHide's Sample Complexity When Mixing Two Private Images

Inspired by InstaHide challenge [Huang, Song, Li and Arora'20], [Chen, Song and Zhuo'20] recently provides one mathematical formulation of InstaHide attack problem under Gaussian images distribution. They show that it suffices to use $O(n_{\mathsf{priv}}^{k_{\mathsf{priv}} - 2/(k_{\mathsf{priv}} + 1)})$ samples to recover one private image in $n_{\mathsf{priv}}^{O(k_{\mathsf{priv}})} + \mathrm{poly}(n_{\mathsf{pub}})$ time for any integer $k_{\mathsf{priv}}$, where $n_{\mathsf{priv}}$ and $n_{\mathsf{pub}}$ denote the number of images used in the private and the public dataset to generate a mixed image sample. Under the current setup for the InstaHide challenge of mixing two private images ($k_{\mathsf{priv}} = 2$), this means $n_{\mathsf{priv}}^{4/3}$ samples are sufficient to recover a private image. In this work, we show that $n_{\mathsf{priv}} \log ( n_{\mathsf{priv}} )$ samples are sufficient (information-theoretically) for recovering all the private images.
Multimodal Pretraining for Dense Video Captioning

Learning specific hands-on skills such as cooking, car maintenance, and home repairs increasingly happens via instructional videos. The user experience with such videos is known to be improved by meta-information such as time-stamped annotations for the main steps involved. Generating such annotations automatically is challenging, and we describe here two relevant contributions. First, we construct and release a new dense video captioning dataset, Video Timeline Tags (ViTT), featuring a variety of instructional videos together with time-stamped annotations. Second, we explore several multimodal sequence-to-sequence pretraining strategies that leverage large unsupervised datasets of videos and caption-like texts. We pretrain and subsequently finetune dense video captioning models using both YouCook2 and ViTT. We show that such models generalize well and are robust over a wide variety of instructional videos.