Depression in / by / for women : agency, feminism and self-help in groups

Depression in / by / for Women: Agency, Feminism and Self-Help in Groups on ensimmäinen väitöstasoinen tutkimus feministisestä terapiasta Suomessa sijoittuen psykologian, sosiaalitieteellisen mielenterveystutkimuksen sekä feministisen tutkimuksen alueille. Perinteisen näkemyksen mukaan feministisen tutkimuksen tulee olla ”naisista, naisten tekemää ja naisille kohdistettua”. Naiset ja masennus -projektitutkimus keskittyy naisten kokemaan masennukseen sisältäen mahdollisen miesten sekä patriarkaalisen hyvinvointivaltion osuuden masennukseen. Masennusta kokevat naiset ovat tutkimuksessa sekä tutkimuksen kohteena että aktiivisia osanottajia, mikä tuo heidän äänensä kuuluville. Tutkimus perustuu vuosien 1994-2000 välisenä aikana kerättyyn 11 ryhmän osallistujia koskevaan kvalitatiivisiin ja kvantitatiivisiin aineistoon. Irmeli Laitinen on ollut suunnittelemassa, keräämässä ja analysoimassa sitä yhdessä projektin muiden jäsenten kanssa. Tutkimuksessa mitattiin kuinka ryhmiin osallistuvien seka masennuksen tunteet että toiminnat muuttuivat yhden vuoden aikana. Tutkimuksen tavoitteena oli sekä masennuksesta kärsivien naisten osallistuminen feministiseen toimintatutkimukseen että ammatillisesti ohjatun oma-apuryhmämenetelmän kehittäminen suomalaiseen mielenterveyspalveluun. Projektin tutkimustulosten mukaan siihen osallistuneet naiset voimaantuivat ymmärtämään itseään sekä saivat luottamusta sosiaaliisiin taitoihinsa. Pidemmällä aikavälillä naisten tunteet muuttuivat myönteisiksi, heidän suhteensa itseensä positiivisemmaksi ja he aktivoituivat fyysisesti. Lisäksi tutkimustulokset viittaavat siihen, että masennus voi johtua näkymättömästä, sukupuolisesti virittyneestä jännitteestä naisystävällisessä hyvinvointivaltiossa paljastaen ”hyvinvointimasennusoireilun”. Suomalaisen sosiologi Erik Allardtin hyvinvointitypologian - having, loving, being – mukaisesti nämä ryhmään osallistuvat naiset eivät koe puutteita niinkään materiaalisessa hyvinvoinnissa (having) vaan pikeminkin suhteiden, sosiaalisen ja emotionaalisen hyvinvoinnin ulottuvuuksilla (loving ja being). Se, että masentuneet naiset pystyvät tuomaan esille pitkään vaiennettuja kokemuksiaan, voi merkitä paljon heidän paranemisessaan ja voimaantumisessaan. Ammatillisesti ohjatut oma-apuryhmät ja naisystävälliset hoitokäytännöt mahdollistivat tämänkaltaisen paranemisprosessin alkamisen tutkimukseen osallistuneissa ryhmissä.

Detection,amplification and sequence homology of sodC in clinical isolates of Salmonella sp

Background & objectives: Periplasmic copper and zinc superoxide dismutase (Cu,Zn-SOD or SodC) is an important component of the antioxidant shield which protects bacteria from the phagocytic oxidative burst. Cu,Zn-SODs protect Gram-negative bacteria against oxygen damage which have also been shown to contribute to the pathogenicity of these bacterial species. We report the presence of SodC in drug resistant Salmonella sp. isolated from patients suffering from enteric fever. Further sodC was amplified, cloned into Escherichia coli and the nucleotide sequence and amino acid sequence homology were compared with the standard strain Salmonella Typhimurium 14028. Methods: Salmonella enterica serovar Typhi (S. Typhi) and Salmonellaenterica serovar Paratyphi (S. Paratyphi) were isolated and identified from blood samples of the patients. The isolates were screened for the presence of Cu, Zn-SOD by PAGE using KCN as inhibitor of Cu,Zn-SOD. The gene (sodC) was amplified by PCR, cloned and sequenced. The nucleotide and amino acid sequences of sodC were compared using CLUSTAL X.Results: SodC was detected in 35 per cent of the Salmonella isolates. Amplification of the genomic DNA of S. Typhi and S. Paratyphi with sodC specific primers resulted in 519 and 515 bp amplicons respectively. Single mutational difference at position 489 was observed between thesodC of S. Typhi and S. Paratyphi while they differed at 6 positions with the sodC of S. Typhimurium 14028. The SodC amino acid sequences of the two isolates were homologous but 3 amino acid difference was observed with that of standard strain S. Typhimurium 14028.Interpretation & conclusions: The presence of SodC in pathogenic bacteria could be a novel candidate as phylogenetic marker.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Detection of a periodic structure hidden in random background: the role of signal amplitude in the matched filter detection method

The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r(0)/Lambda) gt;= 0.11, where r(0) is the coherence length of light on scattering from the rough part and 3 is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a = 0 to small finite values of a. We thus address the importance of the following quantities: `(a)lambda) `, which scales the amplitude of the periodic part with the wavelength of light, and (r(0))Lambda),in determining the detectability of the intensity peaks.

Identification of genetic susceptibility loci for migraine

Migraine is the common cause of chronic episodic headache, affecting 12%-15% of the Caucasian population (41 million Europeans and some half a million Finns), and causes considerable loss of quality of life to its sufferers, as well as being linked to increased risk for a wide range of conditions, from depression to stroke. Migraine is the 19th most severe disease in terms of disability-adjusted life years, and 9th among women. It is characterized by attacks of headache accompanied by sensitivity to external stimuli lasting 4-72 hours, and in a third of cases by neurological aura symptoms, such as loss of vision, speech or muscle function. The underlying pathophysiology, including what triggers migraine attacks and why they occur in the first place, is largely unknown. The aim of this study was to identify genetic factors associated with the hereditary susceptibility to migraine, in order to gain a better understanding of migraine mechanisms. In this thesis, we report the results of genetic linkage and association analyses on a Finnish migraine patient collection as well as migraineurs from Australia, Denmark, Germany, Iceland and the Netherlands. Altogether we studied genetic information of nearly 7,000 migraine patients and over 50,000 population-matched controls. We also developed a new migraine analysis method called the trait component analysis, which is based on individual patient responses instead of the clinical diagnosis. Using this method, we detected a number of new genetic loci for migraine, including on chromosome 17p13 (HLOD 4.65) and 10q22-q23 (female-specific HLOD 7.68) with significant evidence of linkage, along with five other loci (2p12, 8q12, 4q28-q31, 18q12-q22, and Xp22) detected with suggestive evidence of linkage. The 10q22-q23 locus was the first genetic finding in migraine to show linkage to the same locus and markers in multiple populations, with consistent detection in six different scans. Traditionally, ion channels have been thought to play a role in migraine susceptibility, but we were able to exclude any significant role for common variants in a candidate gene study of 155 ion transport genes. This was followed up by the first genome-wide association study in migraine, conducted on 2,748 migraine patients and 10,747 matched controls followed by a replication in 3,209 patients and 40,062 controls. In this study, we found interesting results with genome-wide significance, providing targets for future genetic and functional studies. Overall, we found several promising genetic loci for migraine providing a promising base for future studies in migraine.

Depression and Cognition in Type 2 Diabetes from a Life Course Perspective

Background: Type 2 diabetes is linked to several complications which add to both physical and mental distress. Depression is a common co-morbidity of diabetes which can occur both as a cause and a consequence of type 2 diabetes. Depression has been shown to correlate with glucose regulation and treating depression might prove beneficial for glucose regulation as well as for mental well being. Another complication which might affect diabetes management is cognitive decline. Several risk factors and complications of diabetes might modify the risk for developing cognitive impairment, which is increased 1.5 times among subjects with type 2 diabetes. Type 2 diabetes, depression and impaired cognitive performance have all been linked to low birth weight. This thesis aimed to explore the effects and interactions of birth weight, depression and cognitive ability in relation to type 2 diabetes from a life course perspective. Subjects and methods: Studies I, II and V were part of the Helsinki Birth Cohort Study. 2003 subjects participated in an extensive clinical examination at an average age of 61 years. A standard glucose tolerance test (OGTT) was performed and depressive symptoms were assessed using the Beck Depression Inventory (BDI). In addition data was obtained from child welfare clinics and national registers. A subset of the cohort (n=1247) also performed a test on cognitive performance (CogState ®) at the average age of 64. Studies III and IV were randomised clinical trials where mildly depressed diabetic subjects were treated with paroxetine or placebo and the effect on metabolic parameters and quality of life was assessed. The first trial included 14 women and lasted 10 weeks, while the second trial included 43 subjects, both men and women, and lasted 6 months. Results: Type 2 diabetes was positively associated with the occurrence of depressive symptoms. Among diabetic subjects 23.6% had depressive symptoms, compared to 16.7% of subjects with normal glucose tolerance (OR = 1.77, p<0.001). Formal mediation analysis revealed that cardiovascular disease (CVD) is likely to act as a mediator in the association. Furthermore, low birth weight was found to modify the association between type 2 diabetes, CVD and depression. The association between BDI score and having type 2 diabetes or CVD was twice as strong in the subgroup with low birth weight (≤ 2500g) compared with the group with birth weight > 2500g (p for interaction 0.058). In the six months long randomised clinical trial (study IV) paroxetine had a transient beneficial effect on glycosylated haemoglobin A1c (GHbA1c) and quality of life when compared to placebo after three months of treatment. In study V we found that subjects with known diabetes had a consistently poorer level of cognitive performance than subjects with normal glucose tolerance in most of the tested cognitive domains. This effect was further amplified among those born with a small birth weight (p for interaction 0.002). Conclusions: Type 2 diabetes is associated with a higher occurrence of depressive symptoms compared to subjects with normal glucose tolerance. This association is especially strong among subjects with CVD and those born with a low birth weight. Treating depressed diabetic subjects with paroxetine has no long term effect on glucose regulation. Physicians should be aware of depression as an important co-morbidity of type 2 diabetes. Both depression and the cognitive decline often seen among diabetic subjects are increased if the subject is born with a low birth weight. Physicians should recognise low birth weight as an additional risk factor and modifier of diabetic complications.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

On resampling detection and its application to detect image tampering

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.

Transient signal detection using wigner-ville distribution and wavelet denoising

The problem of detecting an unknown transient signal in noise is considered. The SNR of the observed data is first enhanced using wavelet domain filter The output of the wavelet domain filter is then transformed using a Wigner-Ville transform,which separates the spectrum of the observed signal into narrow frequency bands. Each subband signal at the output of the Wigner-ville block is subjected kto wavelet based level dependent denoising (WBLDD)to supress colored noise A weighted sum of the absolute value of outputs of WBLDD is passed through an energy detector, whose output is used as test statistic to take the final decision. By assigning weights proportional to the energy of the corresponding subband signals, the proposed detector approximates a frequency domain matched filter Simulation results are presented to show that the performance of the proposed detector is better than that of the wavelet packet transform based detector.

Pressure sensor based tsunami detection system: A laboratory study

In this paper, we present the study and implementation of a low-cost system to detect the occurrences of tsunamis at significantly smaller laboratory scale. The implementation is easily scalable for real-time deployment. Information reported in this paper includes the experimentally recorded response from the pressure sensor giving an indication as well as an alarm at remote place for the detection of water turbulence similar to the case of tsunami. It has been found that the system developed works very well in the laboratory scale.

Acoustic emission technique for leak detection in an end shield of a pressurised heavy water reactor

This paper discusses a successful application of the Acoustic Emission Technique (AET) for the detection and location of leak paths present on an inaccessible side of an end shield of a Pressurised Heavy Water Reactor (PHWR). The methodology was based on the fact that air- and water-leak AE signals have different characteristic features. Baseline data was generated from a sound end shield of a PHWR for characterising the background noise. A mock-up end shield system with saw-cut leak paths was used to verify the validity of the methodology. It was found that air-leak signals under pressurisation (as low as 3 psi) could be detected by frequency domain analysis. Signals due to air leaks from various locations of defective end shield were acquired and analysed. It was possible to detect and locate leak paths. The presence of detected leak paths was further confirmed by an alternative test.

Detection of Tsunami Wave Generation and Propagation Using Fiber Bragg Grating Sensors

This paper describes the design and development of a Fiber Bragg Grating (FBG) sensor system for monitoring tsunami waves generated in the deep ocean. An experimental setup was designed and fabricated to simulate the generation and propagation of a tsunami wave. The characteristics and efficiency of the developed FBG sensor was evaluated with a standard commercial Digiquartz sensor. For real time monitoring of tsunami waves, FBG sensors bonded to a cantilever is used and the wavelength shifts (Delta lambda(B)) in the reflected spectra resulting from the strain/pressure imparted on the FBGs have been recorded using a high-speed Micron Optics FBG interrogation system. The parameters sensed are the signal burst during tsunami generation and pressure variations at different places as the tsunami wave propagates away from the source of generation. The results obtained were compared with the standard commercial sensor used in tsunami detection. The observations suggest that the FBG sensor was highly sensitive and free from many of the constraints associated with the commercial tsunameter.

Detection of moisture stress by indicator plots — A simulation

The possibility of advanced indication of moisture stress in a crop by small prepared plots with compacted or partially sand-substituted soils is examined by an analytical simulation. A series of soils and three crops are considered for the simulation. The moisture characteristics of the soils are calculated with an available model. Using average potential evapotranspiration values and a simple actual evapotranspiration model, the onset of moisture stress in the natural and indicator plots is calculated for different degrees of sand substitution and compaction. Cases where sand substitution fails are determined. The effect of intervening rainfall and limited root depth on the beginning of moisture stress is investigated.

Narrowband Detection of Acoustic Source in Shallow Ocean using Vector Sensor Array

The problem of narrowband CFAR (constant false alarm rate) detection of an acoustic source at an unknown location in a range-independent shallow ocean is considered. If a target is present, the received signal vector at an array of N sensors belongs to an M-dimensional subspace if N exceeds the number of propagating modes M in the ocean. A subspace detection method which utilises the knowledge of the signal subspace to enhance the detector performance is presented in thisMpaper. It is shown that, for a given number of sensors N, the performance of a detector using a vector sensor array is significantly better than that using a scalar sensor array. If a target is detected, the detector using a vector sensor array also provides a concurrent coarse estimate of the bearing of the target.