Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Locating System for Cereal Plant Stem Emerging Points’ Detection Using a Convolutional Neural Network

Determining the individual location of a plant, besides evaluating sowing performance, would make subsequent treatment for each plant across a field possible. In this study, a system for locating cereal plant stem emerging points (PSEPs) has been developed. In total, 5719 images were gathered from several cereal fields. In 212 of these images, the PSEPs of the cereal plants were marked manually and used to train a fully-convolutional neural network. In the training process, a cost function was made, which incorporates predefined penalty regions and PSEPs. The penalty regions were defined based on fault prediction of the trained model without penalty region assignment. By adding penalty regions to the training, the network’s ability to precisely locate emergence points of the cereal plants was enhanced significantly. A coefficient of determination of about 87 percent between the predicted PSEP number of each image and the manually marked one implies the ability of the system to count PSEPs. With regard to the obtained results, it was concluded that the developed model can give a reliable clue about the quality of PSEPs’ distribution and the performance of seed drills in fields.
Style Obfuscation by Invariance

The task of obfuscating writing style using sequence models has previously been investigated under the framework of obfuscation-by-transfer, where the input text is explicitly rewritten in another style. A side effect of this framework are the frequent major alterations to the semantic content of the input. In this work, we propose obfuscation-by-invariance, and investigate to what extent models trained to be explicitly style-invariant preserve semantics. We evaluate our architectures in parallel and non-parallel settings, and compare automatic and human evaluations on the obfuscated sentences. Our experiments show that the performance of a style classifier can be reduced to chance level, while the output is evaluated to be of equal quality to models applying style-transfer. Additionally, human evaluation indicates a trade-off between the level of obfuscation and the observed quality of the output in terms of meaning preservation and grammaticality.
Subset Feedback Vertex Set on Graphs of Bounded Independent Set Size

The (\textsc{Weighted}) \textsc{Subset Feedback Vertex Set} problem is a generalization of the classical \textsc{Feedback Vertex Set} problem and asks for a vertex set of minimum (weighted) size that intersects all cycles containing a vertex of a predescribed set of vertices. Although the two problems exhibit different computational complexity on split graphs, no similar characterization is known on other classes of graphs. Towards the understanding of the complexity difference between the two problems, it is natural to study the importance of a structural graph parameter. Here we consider graphs of bounded independent set number for which it is known that \textsc{Weighted Feedback Vertex Set} is solved in polynomial time. We provide a dichotomy result with respect to the size of a maximum independent set. In particular we show that \textsc{Weighted Subset Feedback Vertex Set} can be solved in polynomial time for graphs of independent set number at most three, whereas we prove that the problem remains NP-hard for graphs of independent set number four. Moreover, we show that the (unweighted) \textsc{Subset Feedback Vertex Set} problem can be solved in polynomial time on graphs of bounded independent set number by giving an algorithm with running time $n^{O(d)}$, where $d$ is the size of a maximum independent set of the input graph. To complement our results, we demonstrate how our ideas can be extended to other terminal set problems on graphs of bounded independent set size. Based on our findings for \textsc{Subset Feedback Vertex Set}, we settle the complexity of \textsc{Node Multiway Cut}, a terminal set problem that asks for a vertex set of minimum size that intersects all paths connecting any two terminals, as well as its variants where nodes are weighted and/or the terminals are deletable, for every value of the given independent set number.
Breast Milk Macronutrient Composition and Infant Growth in Rural West Africa

Infants in The Gambia often experience intense growth faltering within the first two years of life, which is strongly related to season of birth. Infants born in the wet season are significantly more likely to experience growth stunting and faltering and are ten times more likely to die in early adulthood than those infants born in the dry season. Women, who burden much of the agricultural workload, must increase physical labor during the wet season to prepare fields and plant the crops for the next season’s harvest. The combined stress of caloric deprivation and intense physical labor during the wet season is energetically taxing on mothers and has been hypothesized to contribute to the differential individual shortand long-term outcomes dependent on season of birth. This study aims to assess different environmental, socioeconomic, and anthropometric variables associated with breast milk macronutrient composition and how these variables then affect infant growth outcomes. Results from this study demonstrate that breast milk is relatively buffered from changes in environment, socioeconomic factors, and maternal anthropometrics. However, examination of longitudinal patterns of milk macronutrients shows evidence of significant interindividual variation. Significant variables in predicting milk macronutrients in this study include infant season of birth, number of livestock per household, and pre and postnatal infant dietary supplementation. In assessing the effect of these macronutrients on infant growth, results demonstrate that infant growth is significantly affected by fat (FAT), protein (PRO), lactose (LAC), and true protein (TRP) along with infant sex, maternal parity and socioeconomic factors
First bone-cracking dog coprolites provide new insight into bone consumption in Borophagus and their unique ecological niche

Borophagine canids have long been hypothesized to be North American ecological ‘avatars’ of living hyenas in Africa and Asia, but direct fossil evidence of hyena-like bone consumption is hitherto unknown. We report rare coprolites (fossilized feces) of Borophagus parvus from the late Miocene of California and, for the first time, describe unambiguous evidence that these predatory canids ingested large amounts of bone. Surface morphology, micro-CT analyses, and contextual information reveal (1) droppings in concentrations signifying scent-marking behavior, similar to latrines used by living social carnivorans; (2) routine consumption of skeletons; (3) undissolved bones inside coprolites indicating gastrointestinal similarity to modern striped and brown hyenas; (4) B. parvus body weight of ~24 kg, reaching sizes of obligatory large-prey hunters; and (5) prey size ranging ~35–100 kg. This combination of traits suggests that bone-crushing Borophagus potentially hunted in collaborative social groups and occupied a niche no longer present in North American ecosystems.
Cost-Sensitive Feature Selection via F-Measure Optimization Reduction

Feature selection aims to select a small subset from the high-dimensional features which can lead to better learning performance, lower computational complexity, and better model readability. The class imbalance problem has been neglected by traditional feature selection methods, therefore the selected features will be biased towards the majority classes. Because of the superiority of F-measure to accuracy for imbalanced data, we propose to use F-measure as the performance measure for feature selection algorithms. As a pseudo-linear function, the optimization of F-measure can be achieved by minimizing the total costs. In this paper, we present a novel cost-sensitive feature selection (CSFS) method which optimizes F-measure instead of accuracy to take class imbalance issue into account. The features will be selected according to optimal F-measure classifier after solving a series of cost-sensitive feature selection sub-problems. The features selected by our method will fully represent the characteristics of not only majority classes, but also minority classes. Extensive experimental results conducted on synthetic, multi-class and multi-label datasets validate the efficiency and significance of our feature selection method.
Flexible IR-HARQ scheme for polar-coded modulation

A flexible incremental redundancy hybrid automated repeat request (IR-HARQ) scheme for polar codes is proposed based on dynamically frozen bits and the quasi-uniform puncturing (QUP) algorithm. The length of each transmission is not restricted to a power of two. It is applicable for the binary input additive white Gaussian noise (biAWGN) channel as well as higher-order modulation. Simulation results show that this scheme has similar performance as directly designed polar codes with QUP and outperforms LTE-turbo and 5G-LDPC codes with IR-HARQ.
Treatment Effect Estimation with Data-Driven Variable Decomposition

One fundamental problem in causal inference is the treatment effect estimation in observational studies when variables are confounded. Control for confounding effect is generally handled by propensity score. But it treats all observed variables as confounders and ignores the adjustment variables, which have no influence on treatment but are predictive of the outcome. Recently, it has been demonstrated that the adjustment variables are effective in reducing the variance of the estimated treatment effect. However, how to automatically separate the confounders and adjustment variables in observational studies is still an open problem, especially in the scenarios of high dimensional variables, which are common in big data era. In this paper, we propose a Data-Driven Variable Decomposition (D$^2$VD) algorithm, which can 1) automatically separate confounders and adjustment variables with a data driven approach, and 2) simultaneously estimate treatment effect in observational studies with high dimensional variables. Under standard assumptions, we show experimentally that the proposed D$^2$VD algorithm can automatically separate the variables precisely, and estimate treatment effect more accurately and with tighter confidence intervals than the state-of-the-art methods on both synthetic data and real online advertising dataset.
High-Speed Single-Molecule Tracking of CXCL13 in the B-Follicle

Soluble factors are an essential means of communication between cells and their environment. However, many molecules readily interact with extracellular matrix components, giving rise to multiple modes of diffusion. The molecular quantification of diffusion in situ is thus a challenging imaging frontier, requiring very high spatial and temporal resolution. Overcoming this methodological barrier is key to understanding the precise spatial patterning of the extracellular factors that regulate immune function. To address this, we have developed a high-speed light microscopy system capable of millisecond sampling in ex vivo tissue samples and submillisecond sampling in controlled in vitro samples to characterize molecular diffusion in a range of complex microenvironments. We demonstrate that this method outperforms competing tools for determining molecular mobility of fluorescence correlation spectroscopy (FCS) and fluorescence recovery after photobleaching (FRAP) for evaluation of diffusion. We then apply this approach to study the chemokine CXCL13, a key determinant of lymphoid tissue architecture, and B-cell-mediated immunity. Super-resolution single-molecule tracking of fluorescently labeled CCL19 and CXCL13 in collagen matrix was used to assess the heterogeneity of chemokine mobility behaviors, with results indicating an immobile fraction and a mobile fraction for both molecules, with distinct diffusion rates of 8.4 ± 0.2 and 6.2 ± 0.3 µm2s−1, respectively. To better understand mobility behaviors in situ, we analyzed CXCL13-AF647 diffusion in murine lymph node tissue sections and observed both an immobile fraction and a mobile fraction with an example diffusion coefficient of 6.6 ± 0.4 µm2s−1, suggesting that mobility within the follicle is also multimodal. In quantitatively studying mobility behaviors at the molecular level, we have obtained an increased understanding of CXCL13 bioavailability within the follicle. Our high-speed single-molecule tracking approach affords a novel perspective from which to understand the mobility of soluble factors relevant to the immune system.
Flow mediated interactions between two cylinders at finite Re numbers

We present simulations of two interacting moving cylinders immersed in a two-dimensional incompressible, viscous flow. Simulations are performed by coupling a wavelet-adapted, remeshed vortex method with the Brinkman penalization and projection approach. This method is validated on benchmark problems and applied to simulations of a master-slave pair of cylinders. The master cylinder's motion is imposed and the slave cylinder is let free to respond to the flow. We study the relative role of viscous and inertia effects in the cylinders interactions and identify related sharp transitions in the response of the slave. The observed differences in the behavior of cylinders with respect to corresponding potential flow simulations are discussed. In addition, it is observed that in certain situations the finite size of the slave cylinders enhances the transport so that the cylinders are advected more effectively than passive tracers placed, respectively, at the same starting position.
L'incertitude des politiques pénales : L'exemple du contentieux stupéfiants

A partir d'enquetes qualitatives menees dans les tribunaux de Lille et de Nanterre sur le traitement des affaires de stupefiants, on s'interroge sur l'incertitude des politiques penales. Apres un bref rappel du socle juridique de l'action publique dans ce domaine, l'article met en evidence la disparite des pratiques et les systemes d'actions qu'elles revelent sur plusieurs plans, les obstacles auxquels se heurte la volonte de construire une action coherente au niveau local. Sans ceder au « localisme », il evoque ensuite les tensions entre les differents niveaux du local et du global en tant qu'elles attestent du mouvement contradictoire qui travaille les politiques penales dans le domaine des drogues.
Transferts de fonctions et mutation idéologique : le Capitole et le Forum d'Auguste

L'analyse de la lex templi (de Mars Ultor) telle que la transmet Dion Cassius montre qu'elle exprime la volonte non seulement d'attirer dans le nouveau forum des activites politiques et des ceremonies liees specifiquement a la guerre, a la victoire et au gouvernement de l'empire, mais aussi d'en faire un espace civique symbolique, en ce sens que les citoyens, soit individuellement, soit collectivement, soit comme membres de l'un des ordines, ont a voir, directement ou indirectement, avec lui. ; La premiere serie de dispositions signifie, pratiquement, le transfert au forum d'Auguste de nombre des fonctions « profanes » du Capitole ; ce dernier cesse d'etre le centre unique de la religion civique et des activites. politiques qui s'y rattachent. Cette depossession partielle a ete l'aboutissement d'un long processus amorce avec le retour des enseignes restituees par les Parthes, et qui coincide avec un enrichissement et un elargissement de l'ideologie developpee autour de Mars. Le role nouveau attribue au dieu trouve dans la seconde serie de dispositions de la lex templi une illustration qui en manifeste toute l'etendue.
Treatment of Epilepsy : Focus on Levetiracetam

− The standard of care for prescribing antiepileptic drugs (AEDs) has come to favor the use of monotherapy when possible; i.e., when comparable efficacy can be achieved with fewer risks of adverse events and drug interactions. Most patients with epilepsy are started on one of the classic AEDs and, if it proves ineffective, another drug is tried, usually as monotherapy. While most of the newer AEDs that have come into clinical use in recent years are initially used as add-on therapy, their success at improving seizure control in combination treatments has led to their cautious use as monotherapy even before they have been approved for this indication. As a first study to determine the potential efficacy of levetiracetam in monotherapy, a withdrawal trial model was used. Patients who achieved adequate seizure control with levetiracetam as add-on therapy in a double-blind, placebo-controlled study entered a monotherapy phase of the trial in which the baseline AED was gradually withdrawn. Also, long-term data of 505 patients who received levetiracetam for refractory partial seizures were reviewed and found to include 49 patients still treated with levetiracetam monotherapy at the end of the study for a duration between 3 months and 5.5 years. Data from patients in the two trials lend supportive evidence that levetiracetam monotherapy is safe and effective for partial seizures.
Use of a monolithic column for the development and validation of a HPLC method for the determination of famotidine, cimetidine and nizatidine in biological fluids

A simple and selective HPLC method, using a monolithic column, was developed for the simultaneous determination of the histamine H2-receptor antagonists: famotidine, cimetidine and nizatidine, in the presence of sulfadimethoxine as internal standard. The separation was performed on a Chromolith Performance RP-18 column (100 mm x 4.6 mm i.d.) with an isocratic mobile phase consisting of 0.05 mol/L acetate buffer (adjusted to pH 6.5 with triethylamine)/methanol/ acetonitrile (85:10:5, v/v/v). The wavelength was set at 230 nm. Linearity was obtained for concentrations between 0.2 to 50 μg/mL and limits of detection were in the range 0.07-0.17 μg/mL. Full validation with respect to linearity, selectivity, detection and quantification limits, accuracy, precision and robustness, the latter using the Youden’s test, was carried out. The method was successfully applied to the determination of the drugs in human serum and urine following solid phase extraction. Average recoveries between 88.0 to 104.4% and 88.0 to 108.0% in serum and urine samples, respectively, were obtained.
Two Ck1δ transcripts regulated by m6A methylation code for two antagonistic kinases in the control of the circadian clock

Significance The most abundant modification in mRNA is the N6-methylation of internal adenosines (m6A), but m6A’s physiological function is unknown for most mRNAs. Here we show that Casein Kinase 1 Delta mRNA (Ck1δ), coding for a critical kinase in the control of circadian rhythms, is regulated by m6A. When m6A is inhibited, the expression of two CK1δ isoforms, uncharacterized until now, increases due to enhanced translation. This increase in CK1δs leads to a slower clock because of increased phosphorylation of the clock protein PER2 at a key residue, leading to the stabilization of PER2 protein. The N6-methylation of internal adenosines (m6A) in mRNA has been quantified and localized throughout the transcriptome. However, the physiological significance of m6A in most highly methylated mRNAs is unknown. It was demonstrated previously that the circadian clock, based on transcription-translation negative feedback loops, is sensitive to the general inhibition of m6A. Here, we show that the Casein Kinase 1 Delta mRNA (Ck1δ), coding for a critical kinase in the control of circadian rhythms, cellular growth, and survival, is negatively regulated by m6A. Inhibition of Ck1δ mRNA methylation leads to increased translation of two alternatively spliced CK1δ isoforms, CK1δ1 and CK1δ2, uncharacterized until now. The expression ratio between these isoforms is tissue-specific, CK1δ1 and CK1δ2 have different kinase activities, and they cooperate in the phosphorylation of the circadian clock protein PER2. While CK1δ1 accelerates the circadian clock by promoting the decay of PER2 proteins, CK1δ2 slows it down by stabilizing PER2 via increased phosphorylation at a key residue on PER2 protein. These observations challenge the previously established model of PER2 phosphorylation and, given the multiple functions and targets of CK1δ, the existence of two isoforms calls for a re-evaluation of past research when CK1δ1 and CK1δ2 were simply CK1δ.
DifNet: Semantic Segmentation by Diffusion Networks

Deep Neural Networks (DNNs) have recently shown state of the art performance on semantic segmentation tasks, however, they still suffer from problems of poor boundary localization and spatial fragmented predictions. The difficulties lie in the requirement of making dense predictions from a long path model all at once since details are hard to keep when data goes through deeper layers. Instead, in this work, we decompose this difficult task into two relative simple sub-tasks: seed detection which is required to predict initial predictions without the need of wholeness and preciseness, and similarity estimation which measures the possibility of any two nodes belong to the same class without the need of knowing which class they are. We use one branch network for one sub-task each, and apply a cascade of random walks base on hierarchical semantics to approximate a complex diffusion process which propagates seed information to the whole image according to the estimated similarities. The proposed DifNet consistently produces improvements over the baseline models with the same depth and with the equivalent number of parameters, and also achieves promising performance on Pascal VOC and Pascal Context dataset. OurDifNet is trained end-to-end without complex loss functions.
Efficacy of Anti-HER2 Agents in Combination With Adjuvant or Neoadjuvant Chemotherapy for Early and Locally Advanced HER2-Positive Breast Cancer Patients: A Network Meta-Analysis

Background Several (neo)adjuvant treatments for patients with HER2-positive breast cancer have been compared in different randomized clinical trials. Since it is not feasible to conduct adequate pairwise comparative trials of all these therapeutic options, network meta-analysis offers an opportunity for more detailed inference for evidence-based therapy. Methods Phase II/III randomized clinical trials comparing two or more different (neo)adjuvant treatments for HER2-positive breast cancer patients were included. Relative treatment effects were pooled in two separate network meta-analyses for overall survival (OS) and disease-free survival (DFS). Results 17 clinical trials met our eligibility criteria. Two different networks of trials were created based on the availability of the outcomes: OS network (15 trials: 37,837 patients); and DFS network (17 trials: 40,992 patients). Two studies—the ExteNET and the NeoSphere trials—were included only in this DFS network because OS data have not yet been reported. The concept of the dual anti-HER2 blockade proved to be the best option in terms of OS and DFS. Chemotherapy (CT) plus trastuzumab (T) and lapatinib (L) and CT + T + Pertuzumab (P) are probably the best treatment options in terms of OS, with 62.47% and 22.06%, respectively. In the DFS network, CT + T + Neratinib (N) was the best treatment option with 50.55%, followed by CT + T + P (26.59%) and CT + T + L (20.62%). Conclusion This network meta-analysis suggests that dual anti-HER2 blockade with trastuzumab plus either lapatinib or pertuzumab are probably the best treatment options in the (neo)adjuvant setting for HER2-positive breast cancer patients in terms of OS gain. Mature OS results are still expected for the Aphinity trial and for the sequential use of trastuzumab followed by neratinib, the treatment that showed the best performance in terms of DFS in our analysis.