Um sistema de tratamento constituído de um reator anaeróbio de mistura completa e um reator anaeróbio compartimentado (ABR) foi operado durante 140 dias para estudar os efeitos do pré-tratamento das águas residuárias de uma indústria química, por carvão ativado em pó (CAP), e suas implicações nos processos de nitrificação e desnitrificação. Utilizou-se, no pré-tratamento do resíduo, duas concentrações de carvão ativado em pó. Para aplicação de 10 mg/l de CAP a remoção de DQO foi de 60% e a de NTK foi de 50%. Nesta fase, os processos de remoção de nitrogênio foram plenamente viabilizados. Para 5 mg/l de CAP a remoção de DQO foi de 44% e a remoção de NTK 46%, neste período se observou inibição por metais pesados e acúmulo de nitrito no sistema. / A treatment system composed of both an aerobic complete-mix reactor and a anaerobic baftled reactor (ABR) was operated for 140 days to study the effects of the treatment of wastewater chemical industry by powdered activate carbon (PAC) and its implications in nitrification - denitrification processes. In the residue preliminary treatment, two concentrations of PAC were used. For the application of 10 mg/l of CAP the removal of COD was 60% and the removal of TKN was 50%. In this phase, the processes of nitrogen removal were possible to be completely carried out. For 5 mg/l of CAP, the removal of COD was 44% and the removal of TKN 46%. In this period, the inhibition by heavy metaIs and nitrite accumulation in the system was observed.

Bakgrund: Barnmorskor och sjuksköterskor världen över möter och vårdar kvinnor som av olika skäl genomför en inducerad abort. Det kan vara en utmaning som kräver både kunskap och stöd för dem som arbetar inom abortvården. Syfte: Syftet med studien var att belysa barnmorskors och sjuksköterskors erfarenheter av att vårda kvinnor i samband med inducerad abort. Ordet erfarenheter innefattar upplevelser och åsikter baserat på erfarenheter. Metod: Studien genomfördes som en kvalitativ metasyntes med metaetnografi som analysmetod. Tjugosju (27) artiklar inkluderades i resultatet. Resultat: Tre huvudkategorier och tio mönster belyser barnmorskors och sjuksköterskors erfarenheter av att vårda kvinnor i samband med inducerad abort. Dessa var att göra ett bra arbete genom att vara ett stöd, att åsidosätta egna värderingar och att skapa goda upplevelser för kvinnan. Barriärer för kvalitativ abortvård i form av negativa attityder från omgivningen, brister i verksamheten, bristande preventivmedelsanvändning, egna känslor och ta emot fostret. Behov hos vårdgivarna i form av stöd och kunskap. Slutsats: Den abortsökande kvinnan är i behov av stöd och icke dömande attityder från vårdgivare. Barnmorskor och sjuksköterskor behöver ha kunskap och få stöd i arbetet med abortvård. Brist på stöd och kunskap hos barnmorskor och sjuksköterskor kan påverka attityder om kvinnors rätt till inducerad abort inom kollegiet på en arbetsplats, vilket i sin tur kan ha en inverkan på den abortsökande kvinnans omvårdnad. / Background : Midwives and nurses all over the world meet with and care for women who, for various reasons, are undergoing induced abortion. It may be a challenge that requires both knowledge and support for those working in abortion care.Objective: To describe midwives and nurses’ experiences of caring for women who undergo induced abortion. The word experience includes perceptions based on experiences. Method: The study was conducted as a qualitative metasynthesis using meta-ethnography as analysis of data. Twenty-seven (27) peer-reviewed scientific articles were included in the result. Result: Three main categories and ten different patterns highlighted the midwives and nurses' experiences of caring for women undergoing an induced abortion. These were doing a good job by being supportive, putting own values aside and with the goal to create good experiences for the woman. Barriers to qualitative abortion care included negative attitudes from the surroundings, own feelings, receiving the fetus and various issues at the abortion care clinics. The third category was the caregivers’ needs which included support and knowledge. Conclusion: The abortion-seeking woman is in need of support and non-judgmental attitudes from caregivers. Midwives and nurses need knowledge and support in the work of abortion care. Lack of support and knowledge can affect midwives and nurses’ attitudes towards induced abortion as a woman’s right, which in turn can affect the women in need of abortion care.

In this work, we study two problems: first is one of the central problem in learning theory of learning sparse parities and the other k-Vector-SUM is an extension of the not oriousk-SUM problem. We first consider the problem of learning k-parities in the on-line mistake-bound model: given a hidden vector ∈ {0,1}nwith|x|=kand a sequence of “questions” a ,a ,12··· ∈{0,1}n, where the algorithm must reply to each question with〈a ,xi〉(mod 2), what is the best trade off between the number of mistakes made by the algorithm and its time complexity? We improve the previous best result of Buhrman et. al. By an exp (k) factor in the timecomplexity. Next, we consider the problem of learning k-parities in the presence of classification noise of rate η∈(0,12). A polynomial time algorithm for this problem (whenη >0 andk=ω(1))is a longstanding challenge in learning theory. Grigorescu et al. Showed an algorithm running in time(no/2)1+4η2+o(1). Note that this algorithm inherently requires time(nk/2)even when the noise rateη is polynomially small. We observe that for sufficiently small noise rate, it ispossible to break the(nk/2)barrier. In particular, if for some function f(n) =ω(logn) andα∈[12,1),k=n/f(n) andη=o(f(n)−α/logn), then there is an algorithm for the problem with running time poly(n)·( )nk1−α·e−k/4.01.Moving on to the k-Vector-SUM problem, where given n vectors〈v ,v ,...,v12n〉over the vector space Fdq, a target vector tand an integer k>1, determine whether there exists k vectors whose sum list, where sum is over the field Fq. We show a parameterized reduction fromk-Clique problem to k-Vector-SUM problem, thus showing the hardness of k-Vector-SUM. In parameterized complexity theory, our reduction shows that the k-Vector-SUM problem is hard for the class W[1], although, Downey and Fellows have shown the W[1]-hardness result for k-Vector-SUM using other techniques. In our next attempt, we try to show connections between k-Vector-SUM and k-LPN. First we prove that, a variant of k-Vector-SUM problem, called k-Noisy-SUM is at least as hard as the k-LPN problem. This implies that any improvements ink-Noisy-SUM would result into improved algorithms fork-LPN. In our next result, we show a reverse reduction from k-Vector-SUM to k-LPN with high noise rate. Providing lower bounds fork-LPN problem is an open challenge and many algorithms in cryptography have been developed assuming its1 2hardness. Our reduction shows that k-LPN with noise rate η=12−12·nk·2−n(k−1k)cannot be solved in time no(k)assuming Exponential Time Hypothesis and, thus providing lower bound for a weaker version of k-LPN

Gli scenari agricoli europei rivelano un crescente interesse per le filiere corte come strumento di promozione dei sistemi alimentari locali. Nonostante i piccoli agricoltori siano la spina dorsale dell'agricoltura europea, gli interventi politici e legislativi che si sono susseguiti nei decenni non hanno sufficientemente tutelato ne promosso la loro attuale posizione in ambito socio-economico. Il presente lavoro mira a fornire un'approfondita analisi del ruolo delle filiere corte all'interno del quadro normativo europeo per comprendere se l’attuale legislazione sostiene o piuttosto inibisce questi sistemi alternativi di produzione e distribuzione alimentare. Muovendo dall'esame della pletora di definizioni attribuite alla filiera corta e soffermandosi su una revisione critica delle più significative riforme della PAC, in particolare alla luce della strategia 'Farm to Fork', vengono identificate nuove priorità che appaiono più favorevoli ai piccoli agricoltori. Lo studio è arrichito da un confronto tra l'approccio adottoato dell'UE - caratterizzato principalmente da strumenti di hard law e misure top-down -, e quello della California ‘socialmente auto-regolato’, in cui gli 'Alternative Food Movements' e le strategie bottom-up sono attori principali nella regolamentazione della filiere corte e del loro impatto sulla comunità. Lo scopo finale é quello di identificare potenziali elementi utili che, se adottati, potrebbero migliorare il modello europeo. / European agricultural landscapes are undergoing fundamental changes, revealing an increasing interest in Short Food Supply Chains as a tool to promote local food systems and products. Despite small farmers are the backbone of agriculture in the EU, both policy leadership and legal interventions have been not sufficiently fostering their position in the socio and economic today’s narrative. The study aims at providing an extensive analysis of the role of SFSCs within the EU legal framework to understand whether EU legislation supports or rather inhibits these alternative systems of production and supply. Moving from the examination of the plethora of SFSC definitions to a critical revision of the most significant CAP reforms, especially in the light of the ‘Farm to Fork’ strategy, new priorities that seem more favorable to small farmers are identified. The study is enriched by a comparison between the EU legal approach - mainly characterized by hard law instruments and top-down measures -, and the Californian ‘socially self-regulated’ approach, where Alternative Food Movements and bottom-up strategies act as the main player in regulating SFSCs and their impact on the community with the aim of identifying potential insights that could improve the EU model.

This thesis examines so called folding neural networks as a mechanism for machine learning. Folding networks form a generalization of partial recurrent neural networks such that they are able to deal with tree structured inputs instead of simple linear lists. In particular, they can handle classical formulas - they were proposed originally for this purpose. After a short explanation of the neural architecture we show that folding networks are well suited as a learning mechanism in principle. This includes three parts: the proof of their universal approximation ability, the aspect of information theoretical learnability, and the examination of the complexity of training. Approximation ability: It is shown that any measurable function can be approximated in probability. Explicit bounds on the number of neurons result if only a finite number of points is dealt with. These bounds are new results in the case of simple recurrent networks, too. Several restrictions occur if a function is to be approximated in the maximum norm. Afterwards, we consider briefly the topic of computability. It is shown that a sigmoidal recurrent neural network can compute any mapping in exponential time. However, if the computation is subject to noise almost the capability of tree automata arises. Information theoretical learnability: This part contains several contributions to distribution dependent learnability: The notation of PAC and PUAC learnability, consistent PAC/ PUAC learnability, and scale sensitive versions are considered. We find equivalent characterizations of these terms and examine their respective relation answering in particular an open question posed by Vidyasagar. It is shown at which level learnability only because of an encoding trick is possible. Two approaches from the literature which can guarantee distribution dependent learnability if the VC dimension of the concept class is infinite are generalized to function classes: The function class is stratified according to the input space or according to a so-called luckiness function which depends on the output of the learning algorithm and the concrete training data. Afterwards, the VC, pseudo-, and fat shattering dimension of folding networks are estimated: We improve some lower bounds for recurrent networks and derive new lower bounds for the pseudodimension and lower and upper bounds for folding networks in general. As a consequence, folding architectures are not distribution independent learnable. Distribution dependent learnability can be guaranteed. Explicit bounds on the number of examples which guarantee valid generalization can be derived using the two approaches mentioned above. We examine in which cases these bounds are polynomial. Furthermore, we construct an explicit example for a learning scenario where an exponential number of examples is necessary. Complexity: It is shown that training a fixed folding architecture with perceptron activation function is polynomial. Afterwards, a decision problem, the so-called loading problem, which is correlated to neural network training is examined. For standard multilayer feed-forward networks the following situations turn out to be NP-hard: Concerning the perceptron activation function, a classical result from the literature, the NP-hardness for varying input dimension, is generalized to arbitrary multilayer architectures. Additionally, NP-hardness can be found if the input dimension is fixed but the number of neurons may vary in at least two hidden layers. Furthermore, the NP-hardness is examined if the number of patterns and number of hidden neurons are correlated. We finish with a generalization of the classical NP result as mentioned above to the sigmoidal activation function which is used in practical applications.

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This dissertation reports on research related to ultrafiltration (UF) membranes in drinking water applications. A pilot-scale investigation identified seasonal surface water quality impacts on UF performance and resulted in the development of a dynamic chemically enhanced backwash protocol for fouling management. Subsequent analysis of UF process data revealed limitations with the use of specific flux, transmembrane pressure (TMP), and other normalization techniques for assessing UF process fouling. A new TMP balance approach is presented that identifies the pressure contribution of membrane fouling and structural changes, enables direct process performance comparisons at different operating fluxes, and distinguishes between physically and chemically unresolved fouling. In addition to the TMP balance, a five component optimization approach is presented for the systematic improvement of UF processes on the basis of TMP variations. Terms are defined for assessing process event performance, a new process utilization term is presented to benchmark UF productivity, and new measures for evaluating maintenance procedures are discussed. Using these tools, a correlation between process utilization and operating pressures was established and a sustainable process utilization of 93.5% was achieved. UF process capabilities may be further enhanced by pre-coating media onto the membrane surface. Silicon dioxide (SiO2) and powdered activated carbon (PAC) are evaluated as precoating materials, and the applicability of the TMP balance for assessing pre-coated membrane performance is demonstrated. The first use of SiO2 as a support layer for PAC in a membrane pre-coating application is presented at the laboratory-scale. SiO2-PAC pre-coatings successfully reduced physically unresolved fouling and enhanced UF membrane organics removal capabilities.

<p dir="ltr">This thesis presents probably approximately correct (PAC) bounds on estimates of the transition kernels of Controlled Markov chains (CMC’s). CMC’s are a natural choice for modelling various industrial and medical processes, and are also relevant to reinforcement learning (RL). Learning the transition dynamics of CMC’s in a sample efficient manner is an important question that is open. This thesis aims to close this gap in knowledge in literature.</p><p dir="ltr">In Chapter 2, we lay the groundwork for later chapters by introducing the relevant concepts and defining the requisite terms. The two subsequent chapters focus on non-parametric estimation. </p><p dir="ltr">In Chapter 3, we restrict ourselves to a finitely supported CMC with d states and k controls and produce a general theory for minimax sample complexity of estimating the transition matrices.</p><p dir="ltr">In Chapter 4 we demonstrate the applicability of this theory by using it to recover the sample complexities of various controlled Markov chains, as well as RL problems.</p><p dir="ltr">In Chapter 5 we move to a continuous state and action spaces with compact supports. We produce a robust, non-parametric test to find the best histogram based estimator of the transition density; effectively reducing the problem into one of model selection based on empricial processes.</p><p dir="ltr">Finally, in Chapter 6 we move to a parametric and Bayesian regime, and restrict ourselves to Markov chains. Under this setting we provide a PAC-Bayes bound for estimating model parameters under tempered posteriors.</p>

Preplaced aggregate concrete (PAC) is produced by grouting high workability cement based grouts among the voids of compacted coarse aggregate mass. Because of its low shrinkage, PAC has been used for many repair jobs like; tunnel lines, dams and bridge piers. Moreover, it has been used for underwater construction. Grout has a major effect on the properties of produced PAC and well defined grout controls the properties of resulted PAC. The effect of types and amount of powder materials, admixtures, sand and water content on the properties of fresh and hardened grout for the production of PAC have been investigated. Tests on hardened grout and PAC properties have also been carried out to investigate the most important effects. A correlation between hardened properties of grout and PAC has also been analyzed. Grout rheology using four different gradation sands at two different cement-sand and at different w/c ratios ratios has been identified experimentally; no added chemical admixtures or mineral additives had first employed, then superplasticizer (SP) was added at 2% and 1%, and finally a combination of 1% SP and pulverized fuel ash (Pfa) at 20% of the cement weight was employed for all mixes. Grout tests have included two point workability tests by the Viskomat NT, flow time funnel test, Colcrete flow meter test, and water bleeding test. After that, eighteen grout mixes with high workability were produced using three different sands at three w/c ratios and two c/s ratios with 1% SP and Pfa at 20% of the cement weight were designed. Eighteen hardened grout and PAC then produced and their compressive strength and sorptivity were tested. Grout rheology can be defined by the rheology of cement paste employed and the internal distance between sand particles. The effect of sand surface texture on grout rheology is important at very low internal distances. Fresh grout yield stress is the most important property which gives the same degree of sensitivity for all grouts regardless the material type and content used in the mix. There are strong relations between compressive strength of grout and PAC, but less correlation between them in sorptivity test because of the effect high quantity of coarse aggregate of PAC. Sorptivity of PAC is low comparing with different kinds of concrete suggesting its advantage for underwater construction. / Libyan High Education Ministry