Synthetic Difference-in-Differences

We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference-in-differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this “synthetic difference-in-differences” estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the asymptotic behavior of the estimator when the systematic part of the outcome model includes latent unit factors interacted with latent time factors, and we present conditions for consistency and asymptotic normality. (JEL C23, H25, H71, I18, L66)

A Model for Pest Control using Integrated Approach: Impact of Latent and Gestation Delays

In this article, we have established a mathematical model using impulsive differential equations for the dynamics of crop pest management in the presence of a pest with its predator and bio-pesticides. The pest population is divided into two subpopulations, namely, the susceptible pests and the infected pests. In this control process, bio-pesticides (generally virus) infect the susceptible pest through viral infection within the pest and make it infected so that predators can consume it quickly. We assume that pest controlling, using this integrated approach, is a delayed process and thus incorporated latent time of susceptible pest and gestation delay of predator in the model as time delay parameters. The system dynamics have been analyzed using qualitative theory: the existence of the equilibrium points and their stability properties has been derived. Hopf bifurcation of the coexisting equilibrium point is presented for both the delayed and non-delayed system. Detail numerical simulations are performed in support of analytical results and illustrate the different dynamical regimes observed in the system. We have observed that the system becomes free of infection when the latent time of the pest is large. Coexisting equilibrium exists for the lower value of latent delay, and it can change the stability properties from stable to unstable when it crosses its critical value. In contrast, gestation delay affects the stability switches of coexisting equilibrium only. The combined effect of the two delays on the system is shown numerically. Also, viral replication rate, infection rate (from virus to pest) is also significant from the pest management perspective. In summary, both the delay is essential for crop pest management, and pest control will be successful with tolerable delays.

Explosion-Induced Neurotrauma (Pathophysiological and Patomorphological Features)

The article presents the results of pathophysiological and pathomorphological features which were studied in experimental blust-induced neurotrauma in rats. The relevance of this study is associated with the frequent blust neurotrauma resulting from the use of explosives in military conflicts. At the same time, neurotrauma is more common, which is clinically manifested by cognitive impairment, even with mild and moderate severity. This, in turn, leads to complications and disability for young people. The purpose of the work was to study the consequences of the air-shock wave influence on the functional and morphological states of the central nervous system. Materials and methods. The studies were carried out on 36 white male Wistar rats 5-7 months old, weighing 180-220 g. The rats were divided into two groups: I – experimental group (n=18), the animals of which were anesthetized with halothane, fixed and explosion-induced neurotraum was simulated by generating a baroacoustic wave with an excess pressure of 26.4 ± 3.6 kPa. II group was a control group (n=18). Functional changes were investigated in the Barnes maze. For pathomorphological examination, brain sections were stained with hematoxylin and eosin. The animals were kept in standard conditions and in the standard diet of the vivarium, all studies were conducted in accordance with modern international requirements and norms of humane treatment of animals (Council of Europe Convention dated 18.03.1986 (Strasbourg); Helsinki Declaration 1975, revised and supplemented in 2000, Law of Ukraine dated 21.02.2006 No. 3447-IV), which is evidenced by an extract from the protocols of the meeting of the commission on biomedical ethics. Results and discussion. Analysis of the results of memory studies in the Barnes maze showed a significant (Р <0.05) increase in the latent time of entering the shelter in rats of the experimental group in the acute and early post-traumatic period, which indicates memory impairment. General characteristics of the rats behavior in the experimental group showed an increase in anxiety and disorientation. The increase in research on "fake shelters" and the chaotic movement around the facility was evidenced. Analysis of frontal histological sections of the rat brain in the dynamics of the explosion-induced neurotrauma development showed the presence of characteristic signs in the form of diffuse microhemorrhages in the hippocampus zone in the acute period of injury, diffuse areas of perivascular and pericellular edema in the early post-traumatic period and paretic dilated capillaries in the structure of the cerebral region on 2nd-3rd week of the post-traumatic period. Conclusion. Thus, quantitative (increased latent time) and qualitative (increased anxiety) signs of impaired orientational-spatial memory and the development of specific pathomorphological signs of explosive brain damage in rats of the experimental group were established

Pramipexole and tolcapone alleviate thermal and mechanical nociception in naive rats.

Introduction: Parkinson&rsquo;s disease (PD) is &#1072; neurodegenerative disorder characterized mainly by its motor symptoms. The non-motor symptoms including pain are increasingly recognized in the last few decades. Existing evidence suggests that the dopaminergic neurotransmission has an essential role in pain control. Aim: The aim of the present study was to investigate the antinociceptive effect of dopaminergic drugs pramipexole and tolcapone against chemical and thermal stimuli in naive rats. Materials and methods: Male Wistar rats divided into 8 groups (n=8): saline; diclofenac 25 mg/kg body weight (bw) (positive control); pramipexole 0.5; 1 and 3 mg/kg bw; tolacapone 5; 15 and 30 mg/kg bw. Paw pressure and plantar tests were performed. Paw withdrawal pressure and latent time were measured. Statistical analysis was done by SPSS 19. Results: In the paw pressure test, pramipexole, in a dose of 1 and 3 mg/kg bw and tolcapone in a dose of 30 mg/kg bw, increased significantly the latency at 1, 2, and 3 hours compared to saline (p<0.05). In the plantar test, only the highest dose of pramipexole reached significance at 3 hours compared to the control rats (p<0.05). In contrast to pramipexole the three experimental groups with tolcapone markedly increased the latent time at 1 and 3 hours compared to saline (p<0.05). Conclusions: Pramipexole and tolcapone reduce mechanical and thermal nociception in na&iuml;ve rats by enhancing dopaminergic neurotransmission at both spinal and supraspinal levels. In addition, tolcapone stimulates noradrenergic mediation which may contribute to its antinociceptive effect.

A triangulation estimation and forecasting framework for agricultural time series

This study proposes a framework implementing triangular estimation for better modeling and forecasting time series. In order to improve the performance of estimation, we employ two sources of triangulation to generate a time series, which is statistically indistinguishable with the latent time series hidden in a system. Thanks to Bayesian hierarchical estimation, which is akin to deep learning but more sophisticate and longer history, the framework has been validated by a large amount of records in vegetable auctions. The hierarchical Bayesian estimation and Monte Carlo Markov Chain particle filters used in hidden Markov model are appreciated during the massive bootstrapping of data. Our results demonstrate excellent estimation performance in discovering hidden states.

COMPARATIVE TEST OF HUMAN CHRORIONIC GONADOTROPHIN (HCG), OVAPRIM, AND SPAWNPRIM BRAND HORMONES ON SANGKURIANG CATFISH ARTIFICIAL SPAWNING (Clarias sp.)

The results of spawning in sangkuriang catfish farming do not always go according to the expected results, as many eggs died before hatcing. Therefore, it is necessary to use spawning hormones which can improve egg quality in order to increase profits in cultivation. This research was aimed to determine the difference on success performance of sangkuriang catfish using HCG, Ovaprim, and Spawnprim. This research used a randomized block design (RAK) with 3 treatments i.e P1 (HCG 500 IU/kg), P2 (Ovaprim 0,5 ml/kg), P3 (Spawnprim 0,5 ml/kg) and 3 groups of repetition i.e K1 (spawning group day-1), K2 (spawning group day-2), and K3 (spawning group day-3). The results of this research showed that using Ovaprim hormone had the highest value than other treatments like on latent time 606±17,78 minutes, egg fertilization percentage 75±2,65%, and egg hatching percentage 69,33±5,69%. Then on egg fecundity and egg diameter showed no significant effect with other treatments.

Estimating the Changing Infection Rate of COVID-19 Using Bayesian Models of Mobility

In order to prepare for and control the continued spread of the COVID-19 pandemic while minimizing its economic impact, the world needs to be able to estimate and predict COVID-19's spread. Unfortunately, we cannot directly observe the prevalence or growth rate of COVID-19; these must be inferred using some kind of model. We propose a hierarchical Bayesian extension to the classic susceptible-exposed-infected-removed (SEIR) compartmental model that adds compartments to account for isolation and death and allows the infection rate to vary as a function of both mobility data collected from mobile phones and a latent time-varying factor that accounts for changes in behavior not captured by mobility data. Since confirmed-case data is unreliable, we infer the model's parameters conditioned on deaths data. We replace the exponential-waiting-time assumption of classic compartmental models with Erlang distributions, which allows for a more realistic model of the long lag between exposure and death. The mobility data gives us a leading indicator that can quickly detect changes in the pandemic's local growth rate and forecast changes in death rates weeks ahead of time. This is an analysis of observational data, so any causal interpretations of the model's inferences should be treated as suggestive at best; nonetheless, the model's inferred relationship between different kinds of trips and the infection rate do suggest some possible hypotheses about what kinds of activities might contribute most to COVID-19's spread.