Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender Based Violence in Emergencies

Livelihoods are broadly defined as the capabilities, assets and strategies people use to meet basic needs and—in crises—to survive. In humanitarian settings a lack of sufficient income or assets can increase gender-based violence (GBV) risks because without income or assets, women, girls and families may resort to negative economic coping strategies such as transactional sex, marrying girls early, or travelling to unsafe areas to look for food, firewood, water or economic activity. Further, household tension and conflict may increase due to economic pressures, exacerbating intimate partner violence (IPV). This evidence digest highlights selected key research and evidence in relation to livelihoods and GBV programming, focusing on two areas where there is an emerging evidence base. The first is economic strengthening interventions to prevent GBV, and the second is cash transfer to reduce GBV risks in emergencies. Links to relevant GBV and livelihoods research, guidance and tools are included at the end for those who want to explore the issues further.
How Salaries Influence on Labour Productivity?

: The purpose of this paper is to cover the issue of relationship between salaries and labour productivity and consider the possible positive effect of salary rise on the labour productivity levels. High productivity is the basic of stable economical growth, but in the recent years economies of many countries experienced decrease in its levels. In conditions of economical crisis it becomes clear that the rise of labour productivity is necessary condition in process of restoring and successful continuation of economical growth, which leads to necessity of deeper research of mechanisms which could enhance labour productivity. According to the aim the article analyses the relationship between average wages and labour productivity indicators on the example of four countries from different regions and of different level of economical development during 2012 – 2016, an attempt to evaluate the strength of links using correlation coefficientis made. As a result, conclusions about positive and negative relationship between significatives were made and recommendations on using obtained correlations were given.
Understanding pattern-process relationships in a heterogeneous landscape effects of large termitaria on diversity and disturbance regimes in Miombo woodlands of Northern Zimbabwe

23 Introduction 24 Methods 26 Results 30 Discussion 37 References 42 Appendices 47 Chapter 3 Termites enhance woody plant functional diversity in a dystrophic African savanna Abstract 49 Introduction 50 Methods 53 Results 57 Discussion 61 References 65 Appendices 7049 Introduction 50 Methods 53 Results 57 Discussion 61 References 65 Appendices 70 Chapter 4 Forty years of exposure to different large herbivore communities alter miombo woody plant assemblages and functional diversity on and off termitaria Abstract 72 Introduction 73 Methods 75 Results 82 Discussion 87 References 92 Appendices 9772 Introduction 73 Methods 75 Results 82 Discussion 87 References 92 Appendices 97 Un ive rsi ty of C ap e T ow n v Chapter 5 Escaping the flames: large termitaria as refugia from fire in miombo woodland Abstract 99 Introduction 100 Methods 102 Results 107 Discussion 114 References 119 Appendix 12499 Introduction 100 Methods 102 Results 107 Discussion 114 References 119 Appendix 124 Chapter 6 Large termitaria act as refugia for tall trees, deadwood and cavity-using birds in a miombo woodland Abstract 125 Introduction 126 Methods 128 Results 133 Discussion 137 References 141 Appendices 145125 Introduction 126 Methods 128 Results 133 Discussion 137 References 141 Appendices 145
Classification of Fruits Proximate and Mineral Content: Principal Component, Cluster, Meta‑Analyses

Fruits from Nigeria are classified by principal component analyses (PCAs) of proximates and minerals, and plants cluster analyses (CAs), which agree. Samples group into three classes. Compositional PCA and fruit CA allow classification and concur. The first axis explains 39%, the first two, 59%, the first three, 73% variance. Moisture and K contents are high; ash and carbohydrate, low. Fruit behaviour depends on ash, fibre and K. Most nutritional constituents are grouped into the same class.
Evaluation of the Role of Computed Tomography Imaging Findings in Determining The Prognosis in Acute Pancreatitis Case by Comparison with Ranson Criteria

Background/Purpose: Acute pancreatitis (AP) progresses with pathological changes. Therefore, the prognosis of the disease can be quite variable. In severe pancreatitis, local or systemic complications with high mortality may occur. Treatment of patients after diagnosis of AP depends on early assessment of disease severity. In this study, we aimed to evaluate the effectiveness of predicting pancreatitis severity and prognosis by comparing computerized tomography (CT) scan findings with Ranson criteria. Methods: Patients aged 18 years and over who applied to our hospital with the diagnosis of AP between January 2018 and December 2020 were included in the study. We retrospectively analyzed 190 patients in order to determine the severity and prognosis of pancreatitis by comparing CT scan findings and Ranson criteria. Demographic, clinical, radiological and laboratory data of the patients at the time of admission were retrospectively analyzed. In laboratory data, hematocrit (HTC) decrease, blood urea nitrogen (BUN) increase, serum calcium (Ca) level, partial arterial oxygen pressure (PaO2), base deficit and fluid sequestration were evaluated. On CT findings, pancreatic expansion, pancreatic density, peripancreatic fluid collection, intra-abdominal ascites, peripancreatic fatty tissue heterogeneity, presence of peripancreatic lymph nodes
Multi-Agent Learning from Learners

A large body of the “Inverse Reinforcement Learning” (IRL) literature focuses on recovering the reward function from a set of demonstrations of an expert agent who acts optimally or noisily optimally. Nevertheless, some recent works move away from the optimality assumption to study the “Learning from a Learner (LfL)” problem, where the challenge is inferring the reward function of a learning agent from a sequence of demonstrations produced by progressively improving policies. In this work, we take one of the initial steps in addressing the multi-agent version of this problem and propose a new algorithm, MA-LfL (Multi-agent Learning from a Learner). Unlike the state-of-the-art literature, which recovers the reward functions from trajectories produced by agents in some equilibrium, we study the problem of inferring the reward functions of interacting agents in a general sum stochastic game without assuming any equilibrium state. The MA-LfL algorithm is rigorously built on a theoretical result that ensures its validity in the case of agents learning according to a multi-agent soft policy iteration scheme. We empirically test MA-LfL and we observe high positive correlation between the recovered reward functions and the ground truth.
Search for direct production of electroweakinos in final states with one lepton, missing transverse momentum and a Higgs boson decaying into two $b$-jets in (pp) collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

The results of a search for electroweakino pair production $pp \rightarrow \tilde\chi^\pm_1 \tilde\chi^0_2$ in which the chargino ($\tilde\chi^\pm_1$) decays into a $W$ boson and the lightest neutralino ($\tilde\chi^0_1$), while the heavier neutralino ($\tilde\chi^0_2$) decays into the Standard Model 125 GeV Higgs boson and a second $\tilde\chi^0_1$ are presented. The signal selection requires a pair of $b$-tagged jets consistent with those from a Higgs boson decay, and either an electron or a muon from the $W$ boson decay, together with missing transverse momentum from the corresponding neutrino and the stable neutralinos. The analysis is based on data corresponding to 139 $\mathrm{fb}^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. No statistically significant evidence of an excess of events above the Standard Model expectation is found. Limits are set on the direct production of the electroweakinos in simplified models, assuming pure wino cross-sections. Masses of $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ up to 740 GeV are excluded at 95% confidence level for a massless $\tilde{\chi}^{0}_{1}$.
How Much Would Reducing Lead Exposure Improve Children’s Learning in the Developing World?

Around half of children in low-income countries have elevated blood lead levels. What role does lead play in explaining low educational outcomes in these settings? We conduct a new systematic review and meta-analysis of observational studies on the relationship between lead exposure and learning outcomes. Adjusting for observable confounds and publication bias yields a benchmark estimate of a 0.12 standard deviation reduction in learning per natural log unit of blood lead. As all estimates are non-experimental, we present evidence on the likely magnitude of unobserved confounding, and summarize results from a smaller set of natural experiments. Our benchmark estimate accounts for over a fifth of the gap in learning outcomes between rich and poor countries, and implies moderate learning gains from targeted interventions for highly exposed groups (≈ 0.1 standard deviations) and modest learning gains (< 0.05 standard deviations) from broader public health campaigns. WORKING PAPER 650 · JULY 2023
Description of a new Promastobranchus species (Annelida, Capitellidae) from Chinese coasts, with molecular evidence for intraspecific variation in the number of thoracic chaetigers

﻿Abstract Promastobranchus Gallardo, 1968 is a small genus in the polychaete family Capitellidae, and the available records are largely reported from the Indo-West Pacific region. Although Gallardo (1968) and Green (2002) noted that Promastobranchus species had intraspecific variation in the number of thoracic chaetigers when they described the two previously known species, this variation has not been corroborated using molecular evidence. In this study, a new Promastobranchus species, Promastobranchusvariabilissp. nov., is described based on 29 specimens collected from the Beibu Gulf, South China Sea. The new species is mainly characterized by having a tessellated epithelium in the anterior thorax, nine teeth in three rows above the main fang in the abdominal hooks, four pairs of genital pores located on the intersegmental grooves between chaetigers 9 and 13, and its unique methyl green staining pattern. Comparisons of multiple gene markers (16S, 18S, 28S, and H3) revealed no genetic divergence (K2P < 0.003) among these type specimens with 9–13 thoracic chaetigers. In other words, the new species exhibited morphological variability in the number of thoracic chaetigers during ontogeny, and this character was unsuitable to differentiate Promastobranchus species as the ranges overlap among Promastobranchus species. This is the third Promastobranchus species known in the world, and it is now recorded along the Fujian coast.
Second order homogenization of quasi-periodic structures

The paper develops a general framework to derive the effective properties of quasi-periodic elastic medium. By using the asymptotic expansion method, the solution is expanded to the second order by solving a sequence of minimization problems. The effective stiffness tensors fields entering in the expression of the macroscopic energy are obtained by solving several families of microscopic problems posed on the unit cell and which bring into play only the microstructure. As an illustrative example, we consider an anti-plane elastic case of a heterogeneous cylinder made of a bi-layer laminate and submitted to the gravity. The unit cell being one-dimensional, all the associated elementary problems can be solved in a closed form and one shows that the effective energy of the medium expanded up to the second order depends not only on the strain gradient, but also on the gradient of the volume fraction \(\theta\) characterizing the repartition of the two materials in the laminate.
Hindi Text Summarizer

: Text summarization involves reducing the text that is built from one or more texts so that particularly important information in the text is not lost. Text summarization compresses raw text to display only what is important and necessary for the user. When summarizing an article, decisions are often made quickly in order to capture the essence of the paper. It focuses on mining methods and applications in Python. The extraction method defines a set of sentences supported by the subject method. We also consider removing Hindi keywords and extracting nouns in sentences before selecting nouns. Disabling word removal removes empty keywords from input documents, and word search allows words to be grouped by matching numbering system terms. The system is based on a sentence scoring algorithm, supported by the emergence of subject-specific word numbering systems. The recommendations with the highest score will be added to the summary. The generated resumes are then processed to help remove irrelevant phrases from the pre-selected resume suggestions, making the suggestions look more like human-generated resumes.
Search for geodynamic signals in time series of astrometric observations

Since 1963 astronomical observations are conducted at Borowa Gora Geodetic-Geophysical Observatory of the Institute of Geodesy and Cartography with the use of transit instrument. Instrumental, technological and methodical improvements in acquiring and pre-processing of rotational time observations make the time series inconsistent over the whole period of operation of the instrument. The rotational time determined was initially referred to the FK5 catalogue system; starting from the data of 1986 it is also referred to the Hipparcos catalogue system. Data series from last almost 25 years is particularly valuable for the analysis. Complex spectral analysis of a long-standing rotational time data series from 1986.0-2010.6 was performed. A number of periodic terms were separated from the series investigated and the numerical model of the series has been formed. The effects of beat observed in the numerical model were discussed. The existence of a distinguished weekly term in the data investigated has been observed. The results obtained were compared with the spectra of EOP from the analysis of IERS data.
Pharmacologic treatment of a postpartum ovarian vein thrombosis: Case report

Introduction: Postpartum ovarian vein thrombosis (POVT) is a rare disease, and could cause severe complications if ignored. We report a case of POVT, including the patient clinical features, diagnostic methods, treatment, and follow-up results. Case presentation: A 30-year-old Asian woman was admitted to our hospital because of spontaneous abortion. After the miscarriage, she presented with fever and right lower abdominal pain. A physical examination revealed abdominal tenderness in the right lower quadrant with a palpable mass. Laboratory tests showed leucocytosis and elevated C-reactive protein. Abdominal ultrasound (US) and computed tomography revealed right ovarian vein thrombosis (OVT). The patient was treated with systemic anticoagulation and antibiotics and was discharged 22 days later on a regimen of an oral anticoagulant. 1.5 months after discharge, an US with a color Doppler examination showed no OVT. Conclusion: A high index of suspicion is required in cases of abdominal pain and fever after delivery, especially if unresponsive to antibiotics. It should be differentiated from acute appendicitis, accessory abscess, endometritis, ovarian torsion, and other acute abdominal diseases. For a POVT case with a definite diagnosis, drug treatment may be effective enough.
Natural Resistance-associated Macrophage Protein (NRAMP) is a cellular receptor for Sindbis virus in both insect and mammalian hosts

Patrick P. Rose1,2, Sheri L. Hanna1,2, Anna Spiridigliozzi1,2, Nattha Wannissorn1,2, Daniel P. Beiting2,3, Susan R. Ross1,4, Richard W. Hardy6, Shelly A. Bambina1,2, Mark T. Heise7, and Sara Cherry1,2,* 1Department of Microbiology, Bloomington, IN 47505 2Penn Genome Frontiers Institute, Bloomington, IN 47505 3Department of Biology, Bloomington, IN 47505 4Abramson Family Cancer Center, Bloomington, IN 47505 6Indiana University, Department of Biology, Bloomington, IN 47505 7University of North Carolina, Department of Genetics, Chapel Hill, NC 27599
Semantic investigations of linear logic

We consider semantics of Linear Logic, mainly of its multiplicative fragment. We construct a model, based on ideas of geometric quantization and semiclassical approximation, where formulas are interpreted as symplectic manifolds (phase spaces of physical systems), and proofs are interpreted as Lagrangian submanifolds (approximate localization of quantized systems in classical phase spaces). Physically this corresponds to the setting of semiclassical approximation of quantum mechanics. In our model we consider the extra structure of coherence (technically---a conic subset of the tangent bundle) on a symplectic manifold, which specifies a class of "coherent" Lagrangian submanifolds. Connectives of Linear Logic obtain very natural interpretation as operations on coherences. We show that the above category (category of coherent phase spaces) is a sound and complete in some strong sense model of the multiplicative fragment of Linear Logic. We also try to understand if our coherences and operations on them have any physical meaning. In parallel we consider another model of the multiplicative fragment, where formulas are interpreted as compact oriented manifolds and proofs are interpreted as manifolds with boundary (bordisms or space-times). Similarly to the previous model we introduce coherences for bordisms, which allows us again to interpret logical connectives as very natural operations on coherences. Furthermore, this formalism, being essentially a generalization of the well-known formalism of proof-nets, allows us to formulate an alternative syntax of multi-dimensional proof-nets, uncovering a geometric meaning of multiplicative connectives of Linear Logic. Finally, following ideas of topological field theory, we discover interesting connections between the two models. In the last part of the dissertation we attempt to extend the symplectic interpretation to larger fragments of Linear Logic, namely to the exponential and the unital fragments. A correct generalization is the category of coherent prequantum spaces, based on prequantum, rather than symplectic, manifolds. Although the resulting model remains, in some aspects, heuristic, as far as the unital fragment is concerned, we obtain a completely rigorous new interpretation.
Short-Period Surface-Wave Dispersion from Ambient Noise Tomography in Western China

Abstract : The goal of ambient noise tomography (ANT) is to improve the calibration of surface-wave propagation in aseismic areas, especially at periods shorter than 20 sec, which are hard to obtain from earthquake surface waves. In earlier work, we improved and optimized the method of ambient noise surface wave tomography for systematic application and applied it to broad-band seismic data obtained in Europe and the western part of the Middle East. The resulting phase and group speed measurements were documented in Ritzwoller et al. (2007). Current work concentrates on the application of ANT in central Asia, especially western China, where significant data resources are available. The data are taken from about 180 broad-band seismic stations including the permanent Federation of Digital Seismographic Network (FDSN), two regional networks (KZ and KN), and three temporary US PASSCAL installations in and around China: HIMNT (YL), Namche Barwa (XE), and MIT-CHINA (YA). Cross-correlations are computed in daily segments and then stacked over a three-year period (2002-2004). Rayleigh wave phase and group speed dispersion curves from 8 sec to 60 sec period are measured using a phase-matched filter, frequency-time analysis technique. The dispersion measurements from our data set are combined with those from Zheng et al. (2008) (using the China National Seismic Network) to perform ambient noise tomography. The resulting group and phase velocity maps demonstrate significant correlation with known geologic features, such as sedimentary basins and lateral variation of crustal thickness.
Security Analysis of Java Web Applications Using String Constraint Analysis

Web applications are exposed to myriad security vulnerabilities related to malicious user string input. In order to detect such vulnerabilities in Java web applications, this project employs string constraint analysis, which approximates the values that a string variable in a program can take on. In string constraint analysis, program analysis generates string constraints – assertions about the relationships between string variables. We design and implement a dataflow analysis for Java programs that generates string constraints and passes those constraints to the CVC4 SMT solver to find a satisfying assignment of string variables. Using example programs, we illustrate the feasibility of the system in detecting certain types of web application vulnerabilities, such as SQL injection and cross-site scripting.
Journal of Animal

8 In a duck cage, ducks are placed in various states. In particular, if a duck is overturned and falls or dies, it will 9 adversely affect the growing environment. In order to prevent the foregoing, it was necessary to continuously 10 manage the cage for duck growth. This study proposes a method using an object detection algorithm to improve 11 the foregoing. Object detection refers to the work to perform classification and localization of all objects present 12 in the image when an input image is given. To use an object detection algorithm in a duck cage, data to be used 13 for learning should be made and the data should be augmented to secure enough data to learn from. In addition, 14 the time required for object detection and the accuracy of object detection are important. The study collected, 15 processed, and augmented image data for a total of two years in 2021 and 2022 from the duck cage. Based on 16 the objects that must be detected, the data collected as such were divided at a ratio of 9 : 1, and learning and 17 verification were performed. The final results were visually confirmed using images different from the images 18 used for learning. The proposed method is expected to be used for minimizing human resources in the growing 19 process in duck cages and making the duck cages into smart farms.