Assessment of key factors responsible for the pest status of the bean flower thrips Megalurothrips sjostedti (Thysanoptera: Thripidae) in West Africa

Megalurothrips sjostedti (Trybom) is an important pest of cowpea (Vigna unguiculata) in West Africa. Three key factors assumed to be responsible for its pest status are analysed, the survival on alternative host-plants during the dry season, the inefficient biotic mortality factors regulating population growth, and the effect of larval feeding on the development of cowpea flower buds. Extensive surveys indicate clearly that M. sjostedti survives the dry season on a wide range of alternative hosts all belonging to the Leguminosae, where it can feed and reproduce. Different antagonists were observed attacking eggs and larvae of M. sjostedti; their impact, however, is low and cannot prevent pest outbreaks. Two undescribed Megaphragma spp., and one Oligosita sp., all trichogrammatid egg parasitoids, were recorded for the first time. The anthocorid Orius sp. was the most important larval predator. No hymenopterous parasitoids could be reared from larvae collected on cowpea and three major alternative hosts, whereas a low percentage of the larvae collected from the flowers of Tephrosia candida, an exotic shrub native to India, were parasitized by the eulophid Ceranisus menes (Walker), also recorded for the first time in Africa. The feeding activity of six larvae of Megalurothrips sjostedti during five days induced the shedding of all flower buds of a cowpea inflorescence. The results of the analysis shed new light on the M. sjostedti pest problem, and the ways to solve it. The lack of efficient antagonists, particularly larval parasitoids known from closely related south-east Asian Megalurothrips spp., and the high damage threshold, indicate that M. sjostedti is a potential target for biological control. However, further studies are needed to investigate the migration of M. sjostedti adults to and from alternative host-plants, in order to reinforce the action of biocontrol with cultural pratice

Noncooperative and Cooperative Transmission Schemes with Precoding and Beamforming

The next generation mobile networks are expected to provide multimedia applications with a high quality of service. On the other hand, interference among multiple base stations (BS) that co-exist in the same location limits the capacity of wireless networks. In conventional wireless networks, the base stations do not cooperate with each other. The BSs transmit individually to their respective mobile stations (MS) and treat the transmission from other BSs as interference. An alternative to this structure is a network cooperation structure. Here, BSs cooperate with other BSs to simultaneously transmit to their respective MSs using the same frequency band at a given time slot. By doing this, we significantly increase the capacity of the networks. This thesis presents novel research results on a noncooperative transmission scheme and a cooperative transmission scheme for multi-user multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM). We first consider the performance limit of a noncooperative transmission scheme. Here, we propose a method to reduce the interference and increase the throughput of orthogonal frequency division multiplexing (OFDM) systems in co-working wireless local area networks (WLANs) by using joint adaptive multiple antennas(AMA) and adaptive modulation (AM) with acknowledgement (ACK) Eigen-steering. The calculation of AMA and AM are performed at the receiver. The AMA is used to suppress interference and to maximize the signal-to-interference-plus-noise ratio (SINR). The AM scheme is used to allocate OFDM sub-carriers, power, and modulation mode subject to the constraints of power, discrete modulation, and the bit error rate (BER). The transmit weights, the allocation of power, and the allocation of sub-carriers are obtained at the transmitter using ACK Eigen-steering. The derivations of AMA, AM, and ACK Eigen-steering are shown. The performance of joint AMA and AM for various AMA configurations is evaluated through the simulations of BER and spectral efficiency (SE) against SIR. To improve the performance of the system further, we propose a practical cooperative transmission scheme to mitigate against the interference in co-working WLANs. Here, we consider a network coordination among BSs. We employ Tomlinson Harashima precoding (THP), joint transmit-receive beamforming based on SINR (signal-to-interference-plus-noise-ratio) maximization, and an adaptive precoding order to eliminate co-working interference and achieve bit error rate (BER) fairness among different users. We also consider the design of the system when partial channel state information (CSI) (where each user only knows its own CSI) and full CSI (where each user knows CSI of all users) are available at the receiver respectively. We prove analytically and by simulation that the performance of our proposed scheme will not be degraded under partial CSI. The simulation results show that the proposed scheme considerably outperforms both the existing noncooperative and cooperative transmission schemes. A method to design a spectrally efficient cooperative downlink transmission scheme employing precoding and beamforming is also proposed. The algorithm eliminates the interference and achieves symbol error rate (SER) fairness among different users. To eliminate the interference, Tomlinson Harashima precoding (THP) is used to cancel part of the interference while the transmit-receive antenna weights cancel the remaining one. A new novel iterative method is applied to generate the transmit-receive antenna weights. To achieve SER fairness among different users and further improve the performance of MIMO systems, we develop algorithms that provide equal SINR across all users and order the users so that the minimum SINR for each user is maximized. The simulation results show that the proposed scheme considerably outperforms existing cooperative transmission schemes in terms of the SER performance and complexity and approaches an interference free performance under the same configuration. We could improve the performance of the proposed interference cancellation further. This is because the proposed interference cancellation does not consider receiver noise when calculating the transmit-receive weight antennas. In addition, the proposed scheme mentioned above is designed specifically for a single-stream multi-user transmission. Here, we employ THP precoding and an iterative method based on the uplink-downlink duality principle to generate the transmit-receive antenna weights. The algorithm provides an equal SINR across all users. A simpler method is then proposed by trading off the complexity with a slight performance degradation. The proposed methods are extended to also work when the receiver does not have complete Channel State Informations (CSIs). A new method of setting the user precoding order, which has a much lower complexity than the VBLAST type ordering scheme but with almost the same performance, is also proposed. The simulation results show that the proposed schemes considerably outperform existing cooperative transmission schemes in terms of SER performance and approach an interference free performance. In all the cooperative transmission schemes proposed above, we use THP to cancel part of the interference. In this thesis, we also consider an alternative approach that bypasses the use of THP. The task of cancelling the interference from other users now lies solely within the transmit-receive antenna weights. We consider multiuser Gaussian broadcast channels with multiple antennas at both transmitter and receivers. An iterative multiple beamforming (IMB) algorithm is proposed, which is flexible in the antenna configuration and performs well in low to moderate data rates. Its capacity and bit error rate performance are compared with the ones achieved by the traditional zero-forcing method

Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials

BACKGROUND: Heterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-specific definition, has led to a multitude of negative randomised controlled trials (RCTs). Investigators have sought to identify heterogeneity of treatment effect (HTE) in RCTs using clustering algorithms. We evaluated the proficiency of several commonly-used machine-learning algorithms to identify clusters where HTE may be detected. METHODS: Five unsupervised: Latent class analysis (LCA), K-means, partition around medoids, hierarchical, and spectral clustering; and four supervised algorithms: model-based recursive partitioning, Causal Forest (CF), and X-learner with Random Forest (XL-RF) and Bayesian Additive Regression Trees were individually applied to three prior ARDS RCTs. Clinical data and research protein biomarkers were used as partitioning variables, with the latter excluded for secondary analyses. For a clustering schema, HTE was evaluated based on the interaction term of treatment group and cluster with day-90 mortality as the dependent variable. FINDINGS: No single algorithm identified clusters with significant HTE in all three trials. LCA, XL-RF, and CF identified HTE most frequently (2/3 RCTs). Important partitioning variables in the unsupervised approaches were consistent across algorithms and RCTs. In supervised models, important partitioning variables varied between algorithms and across RCTs. In algorithms where clusters demonstrated HTE in the same trial, patients frequently interchanged clusters from treatment-benefit to treatment-harm clusters across algorithms. LCA aside, results from all other algorithms were subject to significant alteration in cluster composition and HTE with random seed change. Removing research biomarkers as partitioning variables greatly reduced the chances of detecting HTE across all algorithms. INTERPRETATION: Machine-learning algorithms were inconsistent in their abilities to identify clusters with significant HTE. Protein biomarkers were essential in identifying clusters with HTE. Investigations using machine-learning approaches to identify clusters to seek HTE require cautious interpretation. FUNDING: NIGMS R35 GM142992 (PS), NHLBI R35 HL140026 (CSC); NIGMS R01 GM123193, Department of Defense W81XWH-21-1-0009, NIA R21 AG068720, NIDA R01 DA051464 (MMC)

Evaluation of Externality Costs in Life-Cycle Optimization of Municipal Solid Waste Management Systems

The development of sustainable solid waste management (SWM) systems requires consideration of both economic and environmental impacts. Societal life-cycle costing (S-LCC) provides a quantitative framework to estimate both economic and environmental impacts, by including “budget costs” and “externality costs”. Budget costs include market goods and services (economic impact), whereas externality costs include effects outside the economic system (e.g., environmental impact). This study demonstrates the applicability of S-LCC to SWM life-cycle optimization through a case study based on an average suburban U.S. county of 500 000 people generating 320 000 Mg of waste annually. Estimated externality costs are based on emissions of CO₂, CH₄, N₂O, PM_2.5, PM₁₀, NO_<i>x</i>, SO₂, VOC, CO, NH₃, Hg, Pb, Cd, Cr (VI), Ni, As, and dioxins. The results indicate that incorporating S-LCC into optimized SWM strategy development encourages the use of a mixed waste material recovery facility with residues going to incineration, and separated organics to anaerobic digestion. Results are sensitive to waste composition, energy mix and recycling rates. Most of the externality costs stem from SO₂, NO_<i>x</i>, PM_2.5, CH₄, fossil CO₂, and NH₃ emissions. S-LCC proved to be a valuable tool for policy analysis, but additional data on key externality costs such as organic compounds emissions to water would improve future analyses

Jealousy and violence on university student intimate partners

El efecto deletéreo que tiene la violencia de pareja motiva la exploración empírica de los factores influyentes que puedan ser blancos de prevención. Los objetivos del estudio fueron indagar sobre la violencia en las parejas de estudiantes universitarios y explorar su relación con los celos y otros correlatos. Método: con un diseño de corte transversal, encuestamos a 84 estudiantes de Medicina de la Universidad Nacional de La Plata, Argentina. Los instrumentos utilizados fueron la Conflict in Adolescents Dating Relationships Inventory, la Multidimensional Jealousy Scale y el DSM 5 Cross-cutting level 2: Substance use e items ad hoc. Resultados: Los puntajes de violencia fueron en general bajos, con predominio de los indicadores de violencia verbal emocional y con patrón similar en ambos sexos. Los puntajes totales de celos tuvieron una distribución normal y se relacionaron significativamente con la violencia de pareja. Las manifestaciones de celos con mayor prevalencia fueron las emocionales, especialmente en las mujeres. La valoración de propia y ajena fidelidad y el consumo de marihuana fueron correlatos significativos.The deleterious effect of dating violence motivates the empirical exploration of the influential factors that may be targets of prevention. The aims of this study are to investigate violence in couples of university students and explore their relationship with jealousy and other correlates. Method: with a cross-sectional design, we surveyed 84 medical students from the National University of La Plata, Argentina. The instruments used were the Conflict in Adolescents Dating Relationships Inventory, the Multi dimensional Jealousy Scale and the DSM 5 Cross-cutting level 2: Substance use and ad hoc items. Results: The scores of violence were generally low, with predominance of emotional verbal violence indicators and a similar pattern in both sexes. The total jealous scores had a normal distribution and were significantly related to intimate partner violence. The manifestations of jealousy with greater prevalence were emotional, especially in women. The valuation of own and foreign fidelity and the consumption of marijuana were significant correlates.Facultad de Ciencias Médica

Expectancies regarding the interaction between smoking and substance use in alcohol-dependent smokers in early recovery.

The purpose of this study was to investigate expectancies regarding the interaction between cigarette smoking and use of alcohol among alcohol-dependent smokers in early recovery, using the Nicotine and Other Substances Interaction Expectancies Questionnaire (NOSIE). Participants were 162 veterans, 97% male, with a mean age of 50 years, enrolled in a clinical trial aimed at determining the efficacy of an intensive smoking cessation intervention versus usual care. At baseline, participants were assessed on measures of smoking behavior, abstinence thoughts about alcohol and tobacco use, symptoms of depression, and smoking-substance use interaction expectancies. In addition, biologically verified abstinence from tobacco and alcohol was assessed at 26 weeks. Participants reported that they expected smoking to have less of an impact on substance use than substance use has on smoking (p &lt; .001). Severity of depressive symptoms was significantly associated with the expectancy that smoking provides a way of coping with the urge to use other substances (p &lt; .01). The expectation that smoking increases substance urges/use was predictive of prospectively measured and biologically verified abstinence from smoking at 26 weeks (p &lt; .03). The results add to our knowledge of smoking-substance use interaction expectancies among alcohol-dependent smokers in early recovery and will inform the development of more effective counseling interventions for concurrent alcohol and tobacco use disorders

Smoking abstinence-related expectancies among American Indians, African Americans, and women: Potential mechanisms of disparities in cigarette use

Research has documented tobacco-related health disparities by race and gender. Prior research, however, has not examined expectancies about the smoking cessation process (i.e., abstinence-related expectancies) as potential contributors to tobacco-related disparities in special populations. This cross-sectional study compared abstinence-related expectancies between American Indian (n = 87), African American (n = 151), and White (n = 185) smokers, and between women (n = 231) and men (n = 270) smokers. Abstinence-related expectancies also were examined as mediators of race and gender relationships with motivation to quit and abstinence self efficacy. Results indicated that American Indians and African Americans were less likely than Whites to expect withdrawal effects, and more likely to expect that quitting would be unproblematic. African Americans also were less likely than Whites to expect smoking cessation interventions to be effective. Compared with men, women were more likely to expect withdrawal effects and weight gain. These expectancy differences mediated race and gender relationships with motivation to quit and abstinence self-efficacy. Findings emphasize potential mechanisms underlying tobacco-related health disparities among American Indians, African Americans, and women and suggest a number of specific approaches for targeting tobacco dependence interventions to these populations