Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Efficacy of Deep Neural Networks in Reinforcement Learning Problems

The deep learning community has greatly progressed towards integrating deep neural nets with reinforcement learning, in what is termed ‘deep reinforcement learning. ’ This project aims to investigate the importance of deep neural networks in reinforcement learning. It analyzes the role that deep learning plays in tackling a range of different reinforcement learning problems. By analyzing and evaluating different methods (like Monte Carlo Tree Searches and model-based methods), the project refutes the popular claim that deep reinforcement learning is always the best option to tackle certain problems and explores research papers that support this hypothesis. It identifies the current limitations of deep neural nets, such as overfitting, sparse/shaped reward functions, and sample inefficiency. The project also discusses the potential of Deep-Q Networks, and surprising results in various domains. Thus, in an attempt to compare the merits and problems of deep learning, the project determines the degree to which neural networks are useful in reinforcement learning problems, both now and in the future. Taking the AlphaGo algorithm (and how it beat world Go champion Lee Sedol) case study as a starting point, the project unveils the potential of deep reinforcement learning despite the many challenges it faces today. Therefore, it also aims to come to a conclusion about how deep neural nets in reinforcement learning is likely to develop in the future as data becomes increasingly available and hardware becomes cheaper.
Chemical additives enhance the activity of a Bt‐based biopesticide targeting the beet webworm larvae

Spoladea recurvalis (Fbr.) (Lepidoptera: Crambidae) larvae can cause up to 100% foliage loss on amaranths during severe outbreaks. The Bacillus thuringiensis Subsp. kurstaki product Halt® is a biologically safe biopesticide recommended for the management of Spodoptera exigua (Hübner) and Plutella xylostella (Linnaeus). Spoladea recurvalis larvae are less susceptible to the product. Thirteen chemical additives to improve the efficacy of a Bt spray for control of S. recurvalis were evaluated in laboratory bioassays against second‐instar larvae. All the additives except calcium chloride caused an increase in mortality when applied in mixtures with Bt. Among the seven inorganic salts, boric acid was the only inorganic acid that caused more than 50% larval mortality. Boric acid at a concentration of 0.05% increased the activity of B. thuringiensis by 2.9‐fold. Boric acid had the shortest LT50 values of 5.3 days compared with all other combinations. Two nitrogenous compounds, peptone and sodium nitrate, caused 54 and 51% larval mortalities; however, this increase in efficacy was not significantly different from the mortalities caused by Bt applied without any additive. Urea increased larval mortality from 40% to 51%, although the increase was not significant from a Bt spray application only. Citric acid had no significant effect on the efficacy of Bt spray against S. recurvalis larvae. Overall, among the additives evaluated, the efficacy of Bt spray was most enhanced by boric acid and could be further evaluated under field conditions for validation, and integration into an Integrated Pest Management (IPM) strategy for S. recurvalis management.
The Application of Optimization Techniques in Machine Learning

The past decades have witnessed significantly progress in machine learning, and solving these problems requires the advancing in optimization techniques. High dimensional sparse learning has imposed a great computational challenge to large scale data analysis. In this dissertation, parametric simplex method is applied to solve a broad class of sparse learning approaches, which can be formulated as linear programs parametrized by a regularization parameter. There are serious drawbacks to the existing methods for solving these types of problems as tuning the parameter for the desired solution is very inefficient. The customized parametric simplex method is introduced and it uses the unknown weighting factor as the parameter and provides a powerful and efficient way to address these shortcomings. Although the simplex method has an exponential complexity in the worse case, it has been shown that the parametric simplex method is an appropriate method for these cases when the expected solution is sparse. An R package named fastclime which efficiently solves a variety machine learning problems by the customized parametric simplex method is developed. A convex optimization method named Inexact Peaceman-Rachford Splitting Method (IPRSM) is studied. Similar to the Alternating Direction Method of Multiplier (ADMM), the strictly contractive Peaceman-Rachford Splitting Method (PRSM) is also used to solve a convex minimization problem with linear constraints and a separable objective function. In many applications, it is quite expensive to obtain exact solutions to these subproblems. The inexact methods intend to solve the iterative subproblems when the exact solutions do not exist or they are hard to obtain. Finally, the new graph Perceptron algorithm, a graph estimation method which performs on online binary classification problems is proposed. The new graph Perceptron algorithm is a new kernel based Perceptron derived from online class-action and extend to online graph estimation with a new kernel trick.
Integrative genomic analysis of early neurogenesis reveals a temporal genetic program for differentiation and specification of preplate and Cajal-Retzius neurons

Neurogenesis in the developing neocortex begins with the generation of the preplate, which consists of early-born neurons including Cajal-Retzius (CR) cells and subplate neurons. Here, utilizing the Ebf2-EGFP transgenic mouse in which EGFP initially labels the preplate neurons then persists in CR cells, we reveal the dynamic transcriptome profiles of early neurogenesis and CR cell differentiation. Genome-wide RNA-seq and ChIP-seq analyses at multiple early neurogenic stages have revealed the temporal gene expression dynamics of early neurogenesis and distinct histone modification patterns in early differentiating neurons. We have identified a new set of coding genes and lncRNAs involved in early neuronal differentiation and validated with functional assays in vitro and in vivo. In addition, at E15.5 when Ebf2-EGFP+ cells are mostly CR neurons, single-cell sequencing analysis of purified Ebf2-EGFP+ cells uncovers molecular heterogeneities in CR neurons, but without apparent clustering of cells with distinct regional origins. Along a pseudotemporal trajectory these cells are classified into three different developing states, revealing genetic cascades from early generic neuronal differentiation to late fate specification during the establishment of CR neuron identity and function. Our findings shed light on the molecular mechanisms governing the early differentiation steps during cortical development, especially CR neuron differentiation.
Elevated C-Reactive Protein

Abstract—Recent studies have suggested that elevated plasma C-reactive protein (CRP) levels are associated with the features of insulin resistance syndrome. In the present study, we have examined the contribution of body composition measured by hydrostatic weighing and of abdominal adipose tissue (AT) accumulation assessed by computed tomography to the variation in plasma CRP levels associated with atherogenic dyslipidemia of the insulin resistance syndrome in a sample of 159 men, aged 22 to 63 years, covering a wide range of adiposity (body mass index values from 21 to 41 kg/m2). Plasma CRP levels showed positive and significant correlations with body fat mass (r=0.41, P<0.0001), waist girth (r=0.37, P<0.0001), and visceral AT accumulation measured by computed tomography at L4 to L5 (r=0.28, P<0.0003). Although CRP levels were associated with plasma insulin levels measured in the fasting state and after a 75-g oral glucose load, no significant correlations were found with plasma lipoprotein levels. Final.
Measuring Kruger visitors’ place attachment to specific camps

Tourists become emotionally, physically and socially attached to national parks as they become familiar with the park’s settings and endow it with value. Researchers have pointed out that place attachment leads to environmentally responsible behaviour and higher levels of visitor satisfaction. Therefore, increasing the level of attachment that visitors feel is vital for park and camp managers, and to do so a greater understanding of the various dimensions of it is needed. While attachment to parks has been evaluated previously, attachment to specific camps in parks has not been done. The main purpose of this research study was to measure the extent to which visitors to the Tamboti and Satara camps in the Kruger National Park feel attached to these camps. We also determined whether differences exist between visitors in terms of the level of attachment that they experience towards these camps. Finally, we established the variables that influence place attachment. A self-administered paper-based questionnaire was distributed to visitors to the Tamboti and Satara camps, with 201 questionnaires completed. The results show that visitors generally have a neutral feeling towards the camps. Furthermore, the differences in visitors’ levels of attachment could be attributed to their nationality, wild card membership and frequency of visits. Various managerial implications are drawn and recommendations made on how to increase place attachment to these camps. Conservation implications: This results indicate that visitors do not show particularly strong attachment towards Tamboti and Satara. Recommendations are given for camp managers to increase place attachment to the camps. If camp managers can succeed in fostering stronger levels of attachment to these camps, visitors are more likely to display environmentally responsible behaviour in the camps, with positive conservation implications.
Live Cell Interferometry: A Novel Quantitative Phase Imaging Technique for Rapid Characterizations of Tumor Heterogeneity, Drug Resistance, Cell Fates and Biophysical Properties

Author(s): Huang, Dian | Advisor(s): Teitell, Michael A | Abstract: Cell mass is an important biophysical property that provides a crucial link between external physical measurements and internal cellular processes such as cell cycle progression, division, differentiation and cell death. Advancements in quantitative phase imaging (QPI) techniques have enabled many in-depth studies of cell mass in the context of basic and translational research. This thesis describes the development and implementation of live cell interferometry (LCI) as a novel QPI technique that is high speed, high throughput, precise and label-free. It was validated as a powerful tool in dissecting tumor heterogeneity and drug resistance in patient derived melanoma cell lines. LCI analysis of cell fate in response to mitotic inhibitors provided valuable insights in cancer drug development and dose selection. Furthermore, it was utilized to characterize many other biophysical responses in fundamental research such as cardiomyocyte hypertrophy in cardiac wound healing responses. These studies showcased the unique capabilities and advantages of LCI in applications from bench to bedside.
Dysregulation of external globus pallidus-subthalamic nucleus network dynamics in Parkinsonian mice

Reciprocally connected GABAergic external globus pallidus (GPe) and glutamatergic subthalamic nucleus (STN) neurons form a key, centrally-positioned network within the basal ganglia, a group of subcortical brain nuclei critical for voluntary movement. In Parkinson’s disease (PD) and its models, abnormal rates and patterns of GPe-STN network activity are linked to motor dysfunction. Using cell class-specific optogenetic identification and inhibition approaches during cortical slow-wave activity and activation, we report that in dopamine-depleted mice 1) D2 dopamine receptor expressing striatal projection neurons (D2-SPNs) are hyperactive 2) prototypic parvalbumin (PV)-expressing GPe neurons are excessively patterned by D2-SPNs 3) despite being disinhibited, STN neurons are not hyperactive 4) the STN opposes rather than facilitates abnormal striatopallidal patterning. Together with recent studies, these data argue that in Parkinsonian mice abnormal, temporally offset PV GPe neuron and STN activity results from increased striatopallidal transmission and that compensatory plasticity within the STN prevents its hyperactivity.
Modeling germination of smallflower umbrella sedge (Cyperus difformis L.) seeds from rice fields in California across suboptimal temperatures

Abstract Smallflower umbrella sedge is a prolific C3 weed commonly found in rice fields in 47 countries. The increasing infestation of herbicide-resistant smallflower umbrella sedge populations threatens rice production. Our objectives for this study were to characterize thermal requirements for germination of smallflower umbrella sedge seeds from rice fields in California and to parameterize a population thermal-time model for smallflower umbrella sedge germination. Because the use of modeling techniques is hampered by the lack of thermal-time model parameters for smallflower umbrella sedge seed germination, trials were carried out by placing field-collected seeds in a thermogradient table set at constant temperatures of 11.7 to 41.7 C. Germination was assessed daily for 30 d, and the whole experiment was repeated a month later. Using probit regression analysis, thermal time to median germination [θT(50)], base temperature for germination (Tb), and SD of thermal times for germination [σθT(50)] were estimated from germination data, and model parameters were derived using the Solver tool in Microsoft Excel®. Germination rates increased linearly below the estimated optimum temperatures of 33.5 to 36 C. Estimated Tb averaged 16.7 C, whereas θT(50) equaled 17.1 degree-days and σθT(50) was only 0.1 degree-day. The estimated Tb for smallflower umbrella sedge is remarkably higher than that of japonica and indica types of rice, as well as Tb of important weeds in the Echinochloa complex. Relative to the latter, smallflower umbrella sedge has lower thermal-time requirements to germination and greater germination synchronicity. However, it would also initiate germination much later because of its higher Tb, given low soil temperatures early in the rice growing season in California. When integrated into weed growth models, these results might help optimize the timing and efficacy of smallflower umbrella sedge control measures. Nomenclature: smallflower umbrella sedge; Cyperus difformis L. ; CYPDI; rice; Oryza sativa L.
Linking dissolved organic matter composition and bacterioplankton communities in an Amazon floodplain system

Dissolved organic matter (DOM) is the main substrate for aquatic prokaryotes, fuelling their metabolism and controlling community composition. Amazonian rivers transport and process large fluxes of terrestrial DOM, but little is known about the link between DOM composition and heterotrophic bacteria in the Amazon basin. The aims of this study were to characterize DOM composition and investigate the coupling between DOM and bacterial community composition (BCC) during a complete hydrological cycle in an Amazon floodplain system (lake Janauacá). Our study revealed a clear seasonal pattern in DOM composition through the flood pulse, which affected the amounts of autochthonous and allochthonous inputs and consequently the extent of humification, molecular weight, and aromaticity of the DOM. BCC was tightly coupled to DOM fluorescence, which was also driven by differences over the hydrological cycle, with distinct components and operational taxonomic units being simultaneously more abundant and correlating with a specific season. This coupling was particularly well reflected for three of the four identified fluorescence components, two terrestrial humic‐like components (C1 and C3) and an autochthonous component (C4). Despite clear changes in DOM composition, dissolved organic carbon concentrations tended to be relatively stable throughout the year. Overall, our results suggest that BCC shifts were associated with DOM quality but not with its quantity (that remains relatively constant throughout the year), and that bacteria preferably use labile and freshly produced DOM in lake Janauacá.
Complete mitochondrial genome and phylogenic analysis of Rhinogobius cliffordpopei (Perciformes, Gobiidae)

Abstract The Rhinogobius (Perciformes, Gobiidae), is a species-rich freshwater gobiid genus. In this article, the complete mitochondrial genome (mtDNA) of the Rhinogobius cliffordpopei was first determined. The mtDNA of R. cliffordpopei consisted of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a control region. In the phylogenetic tree, R. cliffordpopei firstly joined with R. brunneus, and next clustered with R. giurinus. Then, they constituted Gobiidae clade with the rest other six species. This relationship consists of taxonomic status. The results would provide basal molecular data for the future research of adaptive evolution in Rhinogobius.
The complete chloroplast genome of coffee tree, Coffea arabica L. ‘Blue Mountain’ (Rubiaceae)

Abstract We presented complete chloroplast genome of Coffea arabica BM1 which is 155,189 bp long and has four subregions: 85,159 bp of large single copy (LSC), and 18,135 bp of small single copy (SSC) regions are separated by 25,946 bp of inverted repeat (IR) regions including 131 genes (86 protein-coding genes, 8 rRNAs, and 37 tRNAs). The overall GC content of the chloroplast genome is 37.4% and those in the LSC, SSC, and IR regions are 35.4, 31.3, and 43.0%, respectively. Low level of cultivar specific sequence variations was found among seven coffee chloroplast genomes.
Molecular Evaluation of some Hybrid Rice Genotypes Using Microsatellite (Ssr) Marker under Normal and Saline Soil Conditions

Eleven hybrid rice combinations were produced by using three cytoplasmic male sterility lines and seven restorers (line x tester mating design) evaluated for agronomic and yield characters under normal and salt soil conditions.The genotypes, Pusa 6A; Giza 178; GZ5121; IR69625A; IR69625A x PR1; Pusa 6A x Giza 178; IR69625A x GZ5121 and IR69625A x PR3 gave the lowest reduction for yield under saline soil condition. However, the genotypes IR69625A x GZ5121 (3.34 t./fed.) and IR69625A x PR3 (3.27 t./fed.) gave the highest yield under saline soil condition if compared with Giza 178 (2.94 t./fed.). Simple sequence repeat (SSR) markers were used to detect possible specific marker to be utilized in the hybrid rice future breeding programs for salt tolerance. However, SSR markers; RM21, RM302 and RM315 generated two (140, 170 bp), three (120, 170, 350 bp) and five DNA fragments (110, 130, 170, 180, 190 bp), respectively. These band can be used as positive or negative specific DNA band on the basis of their appearance or disappearance in the different gene types under study. It is of great interest to mention that the three DNA bands, 140 bp (RM21), 120 bp (RM302) and 190 bp (RM315) are considered as positive specific marker for salt tolerance, while they were appeared in the tolerant genotype (Giza 178) and other hybrid rice genotypes. These salt tolerant specific bands were found in the next genotypes; Pasua 6A x Giza 178, IR68902A, IR68902A x PR1, IR68902A x PR2, IR68902A x PR3, GZ6296R and Giza 182 may be due to heterosis effect, the origin or salt tolerant.Based on phylogenetic tree using similarity index, Pusa 6A x Giza 178, Pusa 6A x PRI, Pusa 6A x PR3 genotypes were found in one cluster and were closely related to the tolerant genotype Giza 178. On the other hand, phylogenetic tree showed that other four clusters were separated and proved that the genotypes PR2; PR3; GZ5121R; IR69625A x PR2; IR69625A x PR3 and IR69625A x GZ5121R were closely related to each other on the basis of their ability to tolerate salt stress.
Experimental and theoretical studies on two-phase flows

This thesis, comprised of two parts, deals with the flow of suspensions. Part I concerns specifically with the stability of a single drop translating through a quiescent, unbounded suspending fluid at low Reynolds number. The evolution of the shape of an initially nonspherical drop as it translates is studied numerically and experimentally. For finite capillary numbers, it is shown that the drop reverts to a sphere provided that the initial deformation is small enough. However, beyond certain critical initial deformation, the drop deforms continuously. For initially prolate shapes, the drop elongates with the formation of a tail; for initially oblate shapes, the drop flattens with the formation of a cavity at its rear. Experiments extend the numerical results. It is found that initially unstable prolate drops break up into multiple droplets, while initially unstable oblate drops deform in double-emulsion drops. Part II of this thesis considers the flow of high concentration solid suspensions through a rectangular channel. By adapting the well-known Laser Doppler Anemometry, an experimental technique is developed to measure the velocity as well as particle volume fraction of the suspension. A crucial element in these experiments is the reduction of the optical turbidity of the suspension. To accomplish this goal, a systematic method based on refractive-index-matching of the two phases is employed. Experimental results show that the velocity profile is blunted while the concentration profile has a maximum near the center. The qualitative features of the experimental data compare reasonably well with theoretical predictions based on the shear-induced particle migration theory.
Excitatory neurons are more disinhibited than inhibitory neurons by chloride dysregulation in the spinal dorsal horn

Neuropathic pain is a debilitating condition caused by the abnormal processing of somatosensory input. Synaptic inhibition in the spinal dorsal horn plays a key role in that processing. Mechanical allodynia – the misperception of light touch as painful – occurs when inhibition is compromised. Disinhibition is due primarily to chloride dysregulation caused by hypofunction of the potassium-chloride co-transporter KCC2. Here we show, in rats, that excitatory neurons are disproportionately affected. This is not because chloride is differentially dysregulated in excitatory and inhibitory neurons, but, rather, because excitatory neurons rely more heavily on inhibition to counterbalance strong excitation. Receptive fields in both cell types have a center-surround organization but disinhibition unmasks more excitatory input to excitatory neurons. Differences in intrinsic excitability also affect how chloride dysregulation affects spiking. These results deepen understanding of how excitation and inhibition are normally balanced in the spinal dorsal horn, and how their imbalance disrupts somatosensory processing.