Quantum, consciousness and panpsychism: a solution to the hard problem

We analyze the results and implications of the combination of quantum and consciousness in terms of the recent QSC analysis. The quantum effect of consciousness is first explored. We show that the consciousness of the observer can help to distinguish the nonorthogonal states under some condition, while the usual physical measuring device without consciousness can’t. The result indicates that the causal efficacies of consciousness do exist when considering the basic quantum process. Based on this conclusion, we demonstrate that consciousness is not reducible or emergent, but a new fundamental property of matter. This provides a quantum basis for panpsychism. Furthermore, we argue that the conscious process is one kind of quantum computation process based on the analysis of consciousness time and combination problem. It is shown that a unified theory of matter and consciousness should include two parts: one is the complete quantum evolution of matter state, which includes the definite nonlinear evolution element introduced by consciousness, and the other is the psychophysical principle or corresponding principle between conscious content and matter state. Lastly, some experimental suggestions are presented to confirm the theoretical analysis of the paper

A quantum method to test the existence of consciousness

As we know, "Who can be said to be a conscious being?" is one of the hard problems in present science, and no method has been found to strictly differentiate the conscious being from the being without consciousness or usual matter. In this short paper, we present a strict physical method based on revised quantum dynamics to test the existence of consciousness, and the principle is to use the distinguishability of nonorthogonal single states. We demonstrate that although the dynamical collapse time can’t be measured by a physical measuring device, a conscious being can perceive it under the assumed QSC condition, thus can distinguish the nonorthogonal single states in the framework of revised quantum dynamics This in principle provides a quantum method to differentiate man and machine, or to test the existence of consciousness. We further discuss the rationality of the assumed QSC condition, and denote that some experimental evidences have indicated that our human being can satisfy the condition. This not only provides some confirmation of our method, but also indicates that the method is a practical proposal, which can be implemented in the near future experiments

Contribution of the antibiotic chloramphenicol and its analogues as precursors of dichloroacetamide and other disinfection byproducts in drinking water

Dichloroacetamide (DCAcAm), a disinfection byproduct, has been detected in drinking water. Previous research showed that amino acids may be DCAcAm precursors. However, other precursors may be present. This study explored the contribution of the antibiotic chloramphenicol (CAP) and two of its analogues (thiamphenicol, TAP; florfenicol, FF) (referred to collectively as CAPs), which occur in wastewater-impacted source waters, to the formation of DCAcAm. Their formation yields were compared to free and combined amino acids, and they were investigated in filtered waters from drinking-water-treatment plants, heavily wastewater-impacted natural waters, and secondary effluents from wastewater treatment plants. CAPs had greater DCAcAm formation potential than two representative amino acid precursors. However, in drinking waters with ng/L levels of CAPs, they will not contribute as much to DCAcAm formation as the μg/L levels of amino acids. Also, the effect of advanced oxidation processes (AOPs) on DCAcAm formation from CAPs in real water samples during subsequent chlorination was evaluated. Preoxidation of CAPs with AOPs reduced the formation of DCAcAm during postchlorination. The results of this study suggest that CAPs should be considered as possible precursors of DCAcAm, especially in heavily wastewater-impacted waters

Analytic Versus Non-Analytic Decision Makers and Their Effect on Win Percentage after In-season Player Acquisitions

This paper examines whether teams with winning records that employ analytic decision makers see a higher increase in win percentage after in-season player acquisitions versus teams that employ non-analytic decision makers. This was accomplished through analyzing the in-season player acquisition data from the MLB and NBA over the last four completed seasons through descriptive and inferential statistics. There was not a significant difference between the two groups in average win percentage after total acquisitions, trades, or signings. Using inferential tests we found no statistical significance between the type of decision maker, and the difference in win percentage after an acquisition

An investigation of particle breakage in loess

The paper presents a detailed experimental investigation of particle breakage in three kinds of loess, i.e., sandy loess, silty loess and clayey loess. It is firstly found that particle breakage can occur within loess in oedometer test, which results in a better-graded soil at the end of the test. Initial breakage stresses for both the silty and clayey loess are less than 0.5 MPa, and about 2 MPa for the sandy loess. The relative breakage (B ) is used to evaluate the particle breakage degree, and it is found that for all the three kinds of loess tested, B increases with the increasing loading stress until it reaches a threshold, after which B tends to keep a constant value. Particles within the loose specimens break more easily than those within the dense ones, especially for the sandy and silty loess. It is also observed that for the specimens reconstituted with previously tested soils, particle breakage degree decreases significantly, which means little particle breakage occurs in the pre-crushed specimens

Do users care about ad's performance costs? Exploring the effects of the performance costs of in-app ads on user experience

Context: In-app advertising is the primary source of revenue for many mobile apps. The cost of advertising (ad cost) is non-negligible for app developers to ensure a good user experience and continuous profits. Previous studies mainly focus on addressing the hidden performance costs generated by ads, including consumption of memory, CPU, data traffic, and battery. However, there is no research on analyzing users’ perceptions of ads’ performance costs to our knowledge. / Objective: To fill this gap and better understand the effects of performance costs of in-app ads on user experience, we conduct a study on analyzing user concerns about ads’ performance costs. / Method: First, we propose RankMiner, an approach to quantify user concerns about specific app issues, including performance costs. Then, based on the usage traces of 20 subject apps, we measure the performance costs of ads. Finally, we conduct correlation analysis on the performance costs and quantified user concerns to explore whether users complain more for higher performance costs. / Results: Our findings include the following: (1) RankMiner can quantify users’ concerns better than baselines by an improvement of 214% and 2.5% in terms of Pearson correlation coefficient (a metric for computing correlations between two variables) and NDCG score (a metric for computing accuracy in prioritizing issues), respectively. (2) The performance costs of the with-ads versions are statistically significantly larger than those of no-ads versions with negligible effect size; (3) Users are more concerned about the battery costs of ads, and tend to be insensitive to ads’ data traffic costs. / Conclusion: Our study is complementary to previous work on in-app ads, and can encourage developers to pay more attention to alleviating the most user-concerned performance costs, such as battery cost

Visual Analytics for Network Security and Critical Infrastructures

A comprehensive analysis of cyber attacks is important for better understanding of their nature and their origin. Providing a sufficient insight into such a vast amount of diverse (and sometimes seemingly unrelated) data is a task that is suitable neither for humans nor for fully automated algorithms alone. Not only a combination of the two approaches but also a continuous reasoning process that is capable of generating a sufficient knowledge base is indispensable for a better understanding of the events. Our research is focused on designing new exploratory methods and interactive visualizations in the context of network security. The knowledge generation loop is important for its ability to help analysts to refine the nature of the processes that continuously occur and to offer them a better insight into the network security related events. In this paper, we formulate the research questions that relate to the proposed solution