Effects of Post Eviction Resettlement on Land-Use and Cover Change in Uganda’s Oil Exploration Areas

Evaluation of the changes in land use and land cover change (LULCC) in respect to oil exploration across the Albertine region in Uganda has been focused around the exploration areas and protected areas, with no attention to the potential impacts of evictees’ activities on resettled areas. This study used LANDSAT images to analyze the land use and land cover changes (LULCC) among the period before eviction (2002 and 2005) at the climax of eviction and resettlements (2005-2011), and during the post-resettlement period (2011-2015) to quantify the impacts of resettlements on the environment. LANDSAT images were processed using ERDAS IMAGINE software and analyzed using ArcGIS 10.1 to determine LULCC in relation to post-eviction resettlement in the study area. Results from the study indicate. The results of the study indicate that vegetation reduced by 33.08 percent, woodland were converted into settlements by 48 percent while farmlands increased by 18.3 percent. Non vegetated areas increased during resettlements however they reduced five years after eviction which indicated the ability of the ecosystem to stabilize. The study proved that post eviction induced resettlements can yield potential environmental effects to resettled areas. It is important therefore to plan and implement other means of additional source of income and construction materials for evictees to abate vegetation clearance and hence rescue the woodland. The study also recommends maintenance of an optimum population and well-planned pre eviction resettlement schemes.

Empowered Stakeholders: Female University Students’ Leadership During the COVID-19-Triggered On-campus Evictions in Canada and the United States

The study of disaster-specific leadership of female university students has been largely neglected,especially during on-campus emergency eviction and evacuation.Based on the COVID-19-triggered,on-campus evictions across Canada and the United States,this cross-national partnership examined the out-of-province/state and international female university students’leadership during the entire eviction process.Through in-depth interviews,this study revealed the female university students’leadership behaviors during three stages:(1)pre-eviction:their self-preparedness formed an emotional foundation to support others;(2)peri-eviction:their attitude and leadership behavior enabled them to facilitate(psychologically and physically)their peers’eviction process;and(3)post-eviction:they continued to support their peers virtually and raised the general public’s awareness regarding the plight of vulnerable and marginalized populations.This article argues that the female university students’leadership that emerged during the eviction process became complementary to and even augmented the universities’official efforts and beyond.This leadership represents empirical evidence that contributes to the existing literature on gender and leadership by demonstrating female youth as empowered stakeholders rather than as merely passive victims.Future studies could develop detailed stratification of gender and age dimensions in order to portray a more comprehensive picture of the younger generation’s leadership in hazards and disaster research and practice.

Proactive eviction of flow entry for SDN based on hidden Markov model

With the fast development of software defined network(SDN),numerous researches have been conducted for maximizing the performance of SDN.Currently,flow tables are utilized in OpenFlows witch for routing.Due to the space limitation of flow table and switch capacity,various issues exist in dealing with the flows.The existing schemes typically employ reactive approach such that the selection of evicted entries occurs when timeout or table miss occurs.In this paper a proactive approach is proposed based on the prediction of the probability of matching of the entries.Here eviction occurs proactively when the utilization of flow table exceeds a threshold,and the flow entry of the lowest matching probability is evicted.The matching probability is estimated using hidden Markov model(HMM).Computersimulation reveals that it significantly enhances the prediction accuracy and decreases the number of table misses compared to the standard Hard timeout scheme and Flow master scheme.

Cowbirds, conservation, and coevolution: potential misconceptions and directions for future research

Avian brood parasitism is a model system for studies of coevolution and ecological interactions between parasites and their hosts. However, recent work may have led to misconceptions concerning the Brown-headed Cowbird (Molothrus ater), the most widely studied brood parasitic bird in the world, and its effects on host species. Potential misconceptions about this species that could affect management issues are as follows: cowbird populations are increasing; cowbirds are relatively new to North America; recently exposed hosts are defenseless against parasitism; cowbirds have caused widespread declines of songbirds; and cowbird control is always effective in increasing the size of endangered host populations. Potential coevolutionary misconceptions are that cowbirds are typically 'host tolerant'; cowbirds evict host nestmates; and the mafia effect is widespread. It is important to clarify these issues because such misconceptions could hinder our understanding of parasite-host interactions, and thus obscure the direction of basic research and of management efforts taken to limit cowbird impacts on endangered species. We discuss these issues and suggest future research directions to enhance our understanding of this fascinating species.

An Investigation of the Factors That Motivated Illegal Settlements in the Mau Forest, Kenya

The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The forest, regarded as the largest indigenous montane forest in east Africa, has been hard hit by land-use changes mainly extensive and ill-planned human settlements. To save the forest, the government has resorted to forced evictions of the settlers. We sought to understand the drivers and causes for the observed illegal settlements in the Mau Forest. To collect data, we conducted focus group discussions and administered household questionnaires on evictees in the South-West and Eastern Mau. Data were analyzed using descriptive and inferential statistics. The results of the binary logistic regression model indicate that Poverty (p = 0.000), Agricultural production (p = 0.000) and Land Given by Government (p = 0.018) contributed significantly to the prediction of people’s motivation of settling in the Mau Forest. In conclusion, population pressure, laxity in forest law enforcement and insecure land tenure and politics were identified as some of the factors that motivated the observed rise in illegal settlements in Mau Forest. Such information on the factors that led to the illegal settlements in Mau Forest would be useful for forest conservation policy makers and managers. It will be a basis upon which interventions can be undertaken to enhance sustainable forest management in Kenya and beyond.

Memway:In-Memory Waylaying Acceleration for Practical Rowhammer Attacks Against Binaries

The Rowhammer bug is a novel micro-architectural security threat, enabling powerful privilege-escalation attacks on various mainstream platforms. It works by actively flipping bits in Dynamic Random Access Memory(DRAM) cells with unprivileged instructions. In order to set up Rowhammer against binaries in the Linux page cache, the Waylaying algorithm has previously been proposed. The Waylaying method stealthily relocates binaries onto exploitable physical addresses without exhausting system memory. However, the proof-of-concept Waylaying algorithm can be easily detected during page cache eviction because of its high disk I/O overhead and long running time. This paper proposes the more advanced Memway algorithm, which improves on Waylaying in terms of both I/O overhead and speed. Running time and disk I/O overhead are reduced by 90% by utilizing Linux tmpfs and inmemory swapping to manage eviction files. Furthermore, by combining Memway with the unprivileged posix fadvise API, the binary relocation step is made 100 times faster. Equipped with our Memway+fadvise relocation scheme,we demonstrate practical Rowhammer attacks that take only 15–200 minutes to covertly relocate a victim binary,and less than 3 seconds to flip the target instruction bit.